Jiakai's Blog

Notes on Getting Four Months of Free ChatGPT Plus

Tue, 25 Aug 2026 00:37:13 -0700

Backstory

This morning I learned from PK大神’s Telegram channel that ChatGPT student verification had reopened.

So I set off on another “Done” run (“Done” being LINUX DO forum slang for successfully claiming a freebie).

I submitted images three times in total, and the last attempt actually made it through SheerID.

Still riding the excitement, I’m writing this post to share what worked.

Lessons Learned

You’ll have to source a US .edu email address yourself; I used one I bought back in 2025 to pass this round of verification. You can search the LINUX DO forum for recent write-ups on how people have been getting US .edu addresses.

I started out by using mainstream AI products to look up a model student currently enrolled at the school behind that .edu domain. The AI has to search the web for the key details — first name, last name, date of birth — because SheerID asks for all of them.

Of the mainstream AI products, I liked Kimi K3’s answer best: it found all three details for an enrolled student at the matching school.

Next I took those three details over to Grok Imagine and generated the matching image.

For the first two failed SheerID attempts, the document type I submitted was School ID card with expiration date.

Following the student info Kimi K3 had given me, I grabbed a matching portrait photo; then I pulled a School ID card that an international student at a US .edu school had posted on Xiaohongshu (Little Red Book) to use as a sample; finally I combined the three details, the portrait, and that student-ID demo, and had Grok Imagine generate the card.

Once it was generated, I had Kimi K3 scrub the image’s metadata and write in simulated realistic metadata. Along the way Kimi K3 refused my request the way GPT and similar models do; phrase what you want more gently and Kimi K3 will most likely go along with it.

Even though the image Kimi K3 processed looked, on the surface, like it met SheerID’s document requirements, it just would not pass.

Your document, or combination of documents, must include:
Your full name as it appears on your school records
The full or abbreviated academic institution name or logo
Proof of current enrollment, shown by one of the following:
A current academic year or current term date
An issue date within the last 90 days
An expiration date that has not passed

I had tinkered up to that point in the morning and gave up. After waking from my afternoon nap, I opened the LINUX DO forum and saw someone share a successful run that used a class schedule instead, so I gave it another shot.

This time I fed Grok Imagine the matching model student’s information plus a recent class schedule posted by a US .edu student on Xiaohongshu, and had it generate a schedule that met SheerID’s requirements.

I had learned my lesson and did not submit it straight away. Instead I uploaded the Kimi K3-scrubbed AI-generated image to ZeroGPT’s AI Image Detector, and it immediately flagged the image as 97% likely to be AI-generated.

I then tried adding noise, cropping, re-photographing it with my phone, and more, but the AI score would not come down. Out of ideas, I stitched the header of the Grok Imagine-generated schedule onto the schedule from the Xiaohongshu post and submitted it to ZeroGPT again — this time the AI score was only 10%.

Before submitting, I had Kimi K3 scrub the metadata on the stitched image once more. Then I submitted the stitched, metadata-scrubbed image for SheerID verification.

A few minutes later, a pleasant surprise: verification passed.

As for payment, I linked the US PayPal account I had registered earlier.

Finally I set myself a to-do reminder to cancel the subscription on December 24, 2026. And with that, this “Done” run was complete.

My first look at ChatGPT Plus was disappointing. GPT on the web has none of the xhigh or pro reasoning-effort options that Business and Pro subscribers get.

Doubao has a freebie of its own today, a 30-day Standard plan. Don’t forget to claim it.

Freebie hunting makes me happy!

AI Tinkering Notes, One Month After Graduation

Sat, 25 Jul 2026 00:31:49 -0700

Preface

It’s been nearly a month since I graduated. Over the past month I’ve tinkered with a lot of AI and piled up quite a few thoughts worth sharing, so I sat down and wrote this article.

Thoughts on AI Trends

My impression right now is that AI vendors care more and more about coding and agent benchmark scores - some have already delayed model releases because those scores didn’t look good. One example is Google’s Gemini 3.5 Pro model.

Personally, I think this emphasis on coding and agents reflects what the market and the public now expect from models: not just chatting and answering questions, but using all kinds of tools to help get tasks done.

I myself was deeply stunned by these agent products more than once in the first half of the year.

For example, my thesis declaration page needed my signature and my advisor’s inserted, but what we got from taking photos wasn’t a background-free version that could be inserted directly. The conventional approach here might be to search Xiaohongshu (Little Red Book) for tips on making background-free signatures, then produce them by hand and insert them; the more advanced approach is to send the signatures straight to an agent product and let the AI make the background-free versions.

Any capable agent product should handle this task with ease. I gave it to both GPT 5.5 in Codex and Claude Opus 4.8 in Claude Cowork, and both produced good background-free signatures. Claude Opus 4.8 in Claude Cowork was more of a “wheelchair” (meaning nanny-level, nothing for you to worry about) and nailed it in one step, while GPT 5.5 in Codex was more cautious and kept asking follow-up questions about my requirements, but in the end both delivered good results.

Another example: having an agent product deploy CLIProxyAPI (CPA), a relay reverse-proxy project. I used the prompt in the image below to have a Claude model deploy the reverse proxy for me and add a web UI display, switching on Auto Mode in Claude Code so it worked on its own, and the final result was very good. Without this kind of agent, I would have had to manually create the folder, write the config file, start the container, and so on. My grad school roommate used a similar prompt and successfully had Codex with GPT 5.5 deploy the CPA relay reverse-proxy project.

The most recent example happened on July 18: I self-hosted OpenClaw and configured the Kimi K3 model from OpenCode, only to be told the model was unavailable. At first I thought OpenCode was falsely advertising and didn’t offer the model at all; in the end, with the help of Claude Code (with Claude Opus 4.8), I found the root cause: OpenClaw hadn’t yet adapted to Kimi K3 through the OpenCode channel, and its model catalog was missing the corresponding entry. Once Claude added the entry, the error disappeared.

Claude

Over the past month, the thing that drove me craziest was Claude models.

To stop worrying about Claude Fable 5 quota, on June 10 I paid 400 yuan to a seller on Xianyu (Chinese secondhand marketplace) for a Max 5x plan topped up through the reseller. After just 2-3 days of use, the Claude Fable 5 ban hit. I remember that day I had gone to an interview for a Guangxi provincial-level public institution job, and on the taxi ride home afterward I saw the push notification about the ban. I had been planning to open a 5-hour Claude window in the car; after seeing the ban, the mood was simply gone. On July 2, Fable 5 was unbanned, and I went back to happily using that Max 5x membership until it expired.

That same day, July 2, I spent another 400 yuan on Xianyu for a new reseller-topped-up Max 5x. This time I wasn’t so lucky: after about 24 hours of use, the account got banned.

The seller offers no warranty against bans - a brutal loss. Afterward I posted on the LINUX DO forum to share this heartbreaking experience. I really am a simp.

But what can you do? To this day, Fable 5 is still the best model overall, all things considered. The middle finger stays raised at Dario and Anthropic, but use it I must. Just make sure your own anti-detection is done thoroughly enough.

On the second day after the ban, I spent 480 yuan on the site of the legendary chirou for a Claude Max 5x account. That account is still alive and well today, and it has never been logged into from any machine in mainland China. It stays parked on a US Windows machine the whole time; I’ve also set up a CPA reverse proxy for it, and I use it on a German VPS as well.

Back in 2024 I wrote a post, Claude Account Suspension Resolution, and it still applies today: for stable use, buy a US VPS and run your Claude services on it the whole time. If the provider has a Windows template, use it directly; if not, install Debian first and then dd-reinstall the disk into Windows. If the speed feels lacking, relay through an optimized route such as DMIT.

In early April this year, I also had one account banned by Anthropic. That ban came from using the Sub2API project, and I haven’t used it since. I remember migrating from the Claude Relay Service project to Sub2API: I had just finished configuring it and started using it when, moments later, it said the account didn’t exist 😅. If your local environment is fine, I generally don’t recommend reverse proxies - a reverse proxy can get you banned, though not always.

I remember during the stretch right after Claude Fable 5 was unbanned, with Ultra Code mode on, Fable 5 sometimes launched 80+ subagents, and I called a halt on the spot. The great Simon Willison also shared a related prompt that has Fable 5 do the planning while handing execution to weaker models to save quota: For all coding tasks use your judgement to decide an appropriate lower power model and run that in a subagent. Personally I think capping the number of subagents is usually enough - say, at no more than 5 - since handing tasks to a weaker model sometimes means it can’t nail them in one hit.

Some fun things I did with Claude models over the past month:

Reviewed nearly all of my personal GitHub projects

Take this very Hugo blog: I ran it through several rounds of checks with Claude Fable 5 and GPT 5.6 Sol Ultra separately. They fixed not only code issues but SEO-related issues too. I barely look at the code anymore - I go by results. As long as what’s displayed looks good, I declare the code fine. 😁

The barrier to writing code really has come down, but you still need real skill of your own to make it hit exactly where you point; otherwise, strong as the models are, you’ll still hit moments where they’re weirdly rigid.

For example, I deliberately had Fable 5 review the RSSHub school-announcement code I’d written with AI a few years back. Fable 5 dug up the problem that “page elements from 10 years ago no longer match the current scraping rules” and filed a Pull Request to fix it. Some of the changes got pushback straight from the open-source maintainer, which shows AI is still fairly rigid. In the scenario in the image below, I served purely as the message courier - the whole conversation was between Fable 5 and the open-source maintainer - and the code was eventually merged into the main branch. My advice is not to copy me: study the craft properly and understand the code before opening a Pull Request, or you’ll add to the open-source maintainers’ burden. This scenario was purely for testing the capability boundaries of the Fable 5 model.

Word got out several times that Fable 5 would be removed from the plans, each time postponed; in the end it’s kept only in the top-tier membership. In early July I thought Fable 5 would go offline on July 7, so I used the Suno v5.5 model to cover a song, “Missing Fei Bo 5” (Fei Bo, a nickname for Fable), with lyrics written by Fable 5; I feel it falls short of the “Missing Fable 5” AI song on Bilibili. via: https://suno.com/s/2SUuwIM3PvMtfnfy

Fable 5 built Scooter Rush, an electric-scooter mayhem game. The whole point of making it: to mock how hard electric scooters are to ride in Nanning, where the road conditions are absurdly complicated. Of all the AI models, the first version Fable 5 built was the one most like Road Rash.

Play it here: https://scooter-rush-nanning.pages.dev

My initial prompt:

hi, claude.

new a folder, then help me build a game.

I want to develop a racing game featuring electric scooters—something like *Road Rash*, but without the violence. The main theme is poking fun at the sheer number of electric scooters in Nanning. Once you pick a character, their scooter is encased in a protective shield; any vehicle or pedestrian that tries to get too close automatically explodes. 😂

There are just so many electric scooters in Nanning; sometimes the traffic conditions leave me speechless.

Having a model finish a task from a single prompt like this isn’t a very objective test of its abilities, but it does give an early glimpse of how well a model understands the real world, and there Fable 5 crushes every other model.

All in all, when Claude Fable 5/Claude Opus 5 isn’t being downgraded over sensitive content, it is the strongest.

GPT

GPT 5.6 was released on July 10. That day I used my UK 48-month discounted ChatGPT Team account to turn on GPT 5.6 Sol Ultra mode (similar to Ultra Code Dynamic Workflows in Claude Code), only to hit the 5-hour limit without finishing a single task, so I spent another 640 yuan on the legendary chirou’s site for a GPT Pro 5x account. OpenAI has since temporarily removed the 5-hour limit - a move that deserves a thumbs up; no more deliberately timing the 5-hour windows.

My overall feeling from using the GPT 5.6 Sol series is that it falls short of Fable 5. Sometimes GPT 5.6 Sol Ultra, while checking and fixing project code, just recklessly bolts on features. Take this very Hugo blog: when GPT 5.6 Sol Ultra was going all out, it went through every single article and caught and fixed errors such as the image URLs Claude Opus 4.5 had written wrong back when it did the i18n internationalization (errors Claude Fable 5 never spotted, mind you) - but then it took the liberty of adding a “Related Posts” section under every article. There were other moments of acting on its own too: GPT 5.6 Sol inexplicably added a privacy page to my blog, and I had to guide it through removing it (see the image below). It’s not as worry-free as Claude; I personally prefer doing Vibe Coding with a wheelchair-grade SOTA model. 😁

On attitude toward users, OpenAI is actually the more decent one: Tibo keeps generously resetting quotas, and the discrimination against Chinese users is nowhere near as severe as Anthropic’s. But in this era focused on coding and agents, the leader is already Anthropic, not OpenAI. ChatGPT Work came almost half a year later than Claude Cowork, even though the two are essentially Codex and Claude Code with a UI on top for ordinary users.

When Claude Fable 5/Opus 5 is downgraded over sensitive content and Kimi K3 keeps throwing 429 errors, I’d say GPT 5.6 Sol is my favorite model.

Had GPT 5.6 Sol Ultra configure Xray for me.

The Xray project thoughtfully provides an AI prompt. I followed it, tossed the task to GPT 5.6 Sol, and let it work fully on its own; when I came back to inspect, every node connected. In that moment I couldn’t help marveling at how badass GPT 5.6 Sol is.

GPT 5.5 in Codex downloaded all the degree-conferral ceremony photos for me.

The university provided a live photo-stream site for the degree-conferral ceremony. I wanted to download all the photos as keepsakes, so I gave the task to both Doubao’s task mode (Seed 2.1 Pro; Doubao is ByteDance’s AI assistant) and GPT 5.5 in Codex.

I even scanned the QR code for Doubao, and it still couldn’t finish the task. GPT 5.5, by contrast, without me scanning anything at all, went straight to analyzing the page source and the APIs, found where the images were hosted, downloaded them all in one go, and compressed them into an archive. Doubao is quite nice for everyday-life scenarios, but on task execution and coding it’s more than a tier behind GPT 5.5.

Analyzed the short comments and long reviews on Douban (China’s film review community) to judge whether Kung Fu Women’s Football (功夫女足) is worth watching.

The final analysis is presented as a ChatGPT Site. URL: https://kungfu-women-football-analysis.jaya.chatgpt.site/

On the web, a ChatGPT Pro membership has an xhigh reasoning-effort option that ChatGPT Business doesn’t. Back in April when I bought a cheap Pro, the Pro-over-Business extra was still the Heavy reasoning effort.

Like Claude Fable 5, GPT 5.6 Sol Ultra took part in the code review of all my projects - as mentioned above, with surprises and disappointments both. It comes back to the same line: when Claude gets sensitive, GPT 5.6 is the best model there is.

The web version of GPT 5.6 Sol Pro is nothing to sneeze at either. Take the question in the image below: it fished the downgrade rules for the Claude Fable 5/Claude Opus 5 models out of huge walls of text on a webpage.

Raising Lobsters

Around the 618 mid-year shopping festival, I bought two services, ArkClaw and Coze, and hooked them into the Feishu (Lark) platform. Coze is decent, I think; ArkClaw is garbage, painfully slow to respond. With CPA as a relay, you can plug custom models into Coze; append the reasoning effort in parentheses after the model ID and you can customize the model’s reasoning effort.

Coze’s personal premium plan lets you spin up one cloud computer and one cloud phone. The cloud phone can log into a Xiaohongshu account and then run some automation, such as monitoring certain accounts for new posts. Of course, the cloud computer and cloud phone have plenty of problems: they don’t really dig deep when researching, opening just a few posts or webpages before hastily wrapping up the task, and the final replies, while looking the part, fall a bit short. Meanwhile, the cloud computer also struggles to extract webpage content - it can only read pages through OCR, or by select-all copying the text through the clipboard.

For now I’m not renewing either plan. I already had a high-spec VPS of my own anyway, so I’ve gone all in on self-hosted Hermes Agent and OpenClaw, hooked into Telegram.

My main use for raising lobsters (slang for running self-hosted claw agents such as OpenClaw): monitoring posts in certain Reddit communities and periodically compiling digests for me.

Any problem while deploying the lobsters gets handed wholesale to the GPT models in Codex or the Claude models in Claude Code.

I also found that these lobster programs can pull off magic like “a Claude model paired with SuperGrok’s X search.”

Hermes Agent can hook into Claude models via Claude subscription login.

Raising lobsters suits monitoring-type tasks; it’s not for writing code, and it’s merely passable for everyday questions - the more you use it, the better it knows you.

Kimi

The Kimi K3 model released on July 16, 2026 is a major victory for Chinese open-source models. Back in June when Kimi K2.7 Code went live, I left my take under the official post: without scaling up the parameter count - staying stuck at 1 trillion - it would be very hard to catch up with Fable 5. Little did I expect that a month later, the ideal would become reality.

I bought the 199 yuan/month plan and gave it a try: like the latest GPT and Claude models, Kimi K3 knows how to call the latest Python SDK for the Gemini API without web access.

Kimi K3 passed the Gomoku test.

A little secret between us: Kimi’s cloud computer can open Google.

Some of you may have subscribed only because of the K3 release; I’d already subscribed a few months earlier. I was busy job hunting back then and needed AI now and then to analyze notices on Chinese webpages, and the Kimi K2.6 Agent solved a lot of those needs. Even then I held huge expectations for Kimi. Among homegrown Chinese AI, of the agent services aimed at individual users, Kimi has the best task completion.

The Kimi service has a drawback too: user data is used to improve the model by default, with no option to opt out of training.

If you value privacy, the Kimi service may not be for you. But Kimi K3 will be officially open-sourced on July 27, 2026, and then you can pick an API service from a hosting provider that protects user privacy. In this day and age there’s no absolute privacy to speak of; even when a vendor offers an opt-out from model training, I doubt it’s honored all that faithfully. Where does the Anthropic Economic Index come from? From analyzing user data, of course 😁.

On the personal-project front, I recently needed to auto-grind online course videos. With Claude and GPT both being sensitive about it, I had Kimi K3 with the Kimi WebBridge extension analyze the page structure and write me a Tampermonkey userscript, then had Claude Fable 5 and Kimi discuss it over multiple rounds. In the end Kimi K3 delivered the userscript and published it on Greasy Fork. The course videos have been grinding away for a whole afternoon now - as long as the browser has the right page open, the grind starts automatically.

Sometimes I can’t help lamenting that Anthropic and OpenAI are hamstringing themselves - far too closed off, unlocking the relevant security capabilities only for users who have passed a cybersecurity certification.

Summary

My personal ranking of LLMs for coding and agent use is shown below:

That’s about it for this past month of AI tinkering notes. As new insights come along, I’ll keep sharing.

Trying Out Perplexity Max

Mon, 08 Jun 2026 18:05:58 +0800

Backstory

In February 2026, Perplexity launched features like Model Council, but restricted them to Max subscribers only. Over the following months in March and April, I spotted some discounted Perplexity Enterprise Max listings on Xianyu (a Chinese secondhand marketplace), but I was too busy to pull the trigger. After the May Day holiday, cheap Perplexity Max memberships popped up again on Xianyu and other resale platforms, so I spent 600 RMB (~$82 USD) to try Perplexity Max for one month. [Note: I later saw listings under 500 RMB — early adopters pay more, latecomers get discounts.]

TL;DR

Perplexity Max has its merits, but not many. Perhaps because I’d already been wowed by Claude Cowork and Codex, Perplexity Max’s features didn’t really move the needle for me.

If you want a low-cost way to experience something like Model Council, check out Model Fusion on OpenRouter.

If you want the model council to have better context from web searches, Perplexity Max might be worth trying. Perplexity is the OG of AI search after all, and the quality of its web retrieval layer is a genuine moat. Note: OpenRouter’s Model Fusion can also enable web access and adjust reasoning intensity.

When using Perplexity’s regular Search, I recommend querying in English (you can use the Immersive Translate extension + triple-space tap to quickly convert Chinese input to English) and setting the model reply preference to Chinese. After all, nobody wants Perplexity citing content from low-quality sources like CSDN.

I also tried personalized custom instructions, but GPT 5.5 Thinking and Claude Opus 4.8 Thinking in Perplexity’s regular Search don’t always follow them well. They see you asking in Chinese and start searching for Chinese content, even when English would yield better results for the query. Computer, on the other hand, follows custom instructions much more reliably.

My Perplexity custom instructions are shown below, written by the Claude Opus model within Perplexity. The main goal is to prioritize high-quality English sources.

Search Strategy:
1. Regardless of the language I use to ask, ALWAYS translate my query into English first and run the web search in English as the primary search.
2. Prioritize high-quality English-language sources (official docs, reputable media, academic sites, GitHub, Stack Overflow, Reddit, etc.).
3. Only run a Chinese-language search as a supplementary pass when the topic is China-specific (local policy, domestic products, Chinese celebrities, etc.) or when English sources are insufficient.
4. Always reply to me in 简体中文, but keep proper nouns, technical terms and quotes in their original English form.
5. When citing, prefer English sources; clearly mark which citations come from Chinese sources.

The Claude Opus model inside Perplexity appears to be genuine (Claude models don’t distinguish between Chinese and English quotation marks), but the reasoning intensity feels low. Even though I often assigned the same tasks to Perplexity Computer, I still ended up preferring results from Claude Cowork and Codex.

Perplexity Computer Key Specs

The cloud machine is a headless Linux server with 2 CPU cores, ~8GB RAM, and ~20GB disk.
Each Computer session gets a dedicated VM, destroyed after the task completes.
The cloud machine IP is an AWS US IP (i.e., Perplexity running in a US IP environment).
The machine comes pre-loaded with tools like Python 3 and curl.
Claude Code and Codex are installed but not logged in.

Highlights and Interesting Use Cases

Cross-validation with Model Council when things are ambiguous

A typical Model Council response consists of four parts: Where Models Agree, Where Models Disagree, Unique Discoveries (shown when a model has a unique finding), and Comprehensive Analysis.

According to users on the r/perplexity_ai subreddit, the monthly Model Council quota is likely 50 or 100 uses. After a month, I never hit the limit — in practice, there just aren’t that many ambiguous questions that warrant a committee discussion. I used it most when preparing for a computer science teaching certification exam, reviewing university-level CS knowledge and cross-checking things I was unsure about.

When your own knowledge can’t verify whether a single model’s response is accurate, having models brainstorm and debate with each other to produce a comprehensive and more trustworthy analysis is genuinely valuable.

Perplexity Computer orchestrating a Code CLI for programming

I set the Computer’s orchestration model to Claude Opus 4.8, had it update Codex and set the Codex model to 5.5 xhigh, then assisted it with my ChatGPT Team device authorization login.

From there, it was Claude Opus 4.8 directing GPT 5.5 in Codex to handle the coding task.

The task was building a birthday celebration website — a single-page site featuring birthday wishes, a letter, a photo gallery, and interactive candle lighting. The final result turned out quite nice.

But is it really necessary to use Perplexity Max’s Computer for this kind of nesting? Obviously not — you could just develop locally with Claude Code and have Codex supervise each step.

Perplexity Mac client controlling WeChat to chat with contacts

On the first day I got the Perplexity Max account, I tested whether it could operate apps like WeChat. After running for quite a while, Computer managed to send WeChat messages to contacts. The screenshot shows it messaging the vendor who sold me the Perplexity Max account.

But the whole process was noticeably less smooth than Claude Cowork — scripted app control was slow. Claude Cowork is the smoothest AI tool I’ve used for operating WeChat, with Codex coming in second.

After installing the Perplexity Mac client, you can use your local Mac as Perplexity Computer’s work environment. I didn’t explore this much, since I trust Claude Cowork and Codex more.

Using Perplexity Computer for scheduled website monitoring

During a recent job search, I needed to watch for new announcements on a website. To get notified immediately when new postings appeared, I had Perplexity Computer check the announcement list every hour and push notifications to a Telegram bot.

The underlying model for scheduled tasks is GPT 5.2 — presumably to save costs, since GPT 5.2 is cheaper than 5.4 and 5.5.

Perplexity Computer drawing on tldraw

Drawing cats stroke by stroke on the tldraw website — the left is Claude Sonnet 4.6’s masterpiece, the right is Claude Opus 4.8’s masterpiece.

Visualizations in Perplexity

Stocks, weather, and other information are presented with visual info cards.

Academic database integration

Researchers can specify sources like Wiley to accelerate their work. I don’t do academic research, so I barely used this feature.

Drawbacks

The Perplexity mobile app defaults Computer’s orchestration model to Claude Sonnet 4.6

As of June 8, 2026, the Perplexity mobile app still can’t specify the orchestration model for Computer like the web version can — there’s simply no model selection option. When probed, the base model turns out to be Claude Sonnet 4.6. Perplexity is being too stingy here.

No cloud desktop interface like Manus

For example, I assigned Perplexity Computer to research user feedback about Perplexity Max on Xiaohongshu (a Chinese social platform). The login QR code was delivered as a screenshot.

It’s essentially a cloud computer like Manus, but all you get are screenshots at most. The user interaction experience is pretty bad.

Limited context window

Remember to enable the extended context window for Computer in settings. Without it, context gets compressed frequently and key information can be lost.

From my research, Perplexity’s context window appears to be only 32k.

Final Thoughts

After a month with Perplexity Max, the mystique has worn off. Everything Perplexity Computer can do, Claude Cowork and Codex can also do — and do better. It’s similar to OpenClaw and Hermes Agent, which can’t match Claude Cowork and Codex in terms of results. Those open-source agents at least have the advantage of being open-source, whereas Perplexity Computer is closed-source.

I’ve seen some Chinese media outlets flip-flopping on Perplexity: one moment calling it a doomed API wrapper, the next praising Model Council and Computer as proof it’s alive and strong. Looking at the trajectory over recent months, I’m not optimistic about the long-term competitiveness of cloud-based agent execution environments like Perplexity Computer. What Computer can do today, Claude Cowork and Codex can largely do as well, and in my experience, often better. The one feature I genuinely appreciate is Model Council — having top-tier models discuss and answer your questions together is a solid experience. Combined with Perplexity’s professional academic databases, it might serve academic researchers particularly well.

That said, my conclusion carries personal bias. For non-technical users, Perplexity Computer’s “zero-config, works out of the box” approach might actually be quite appealing.

These are my observations from nearly a month of use. If you want to try Perplexity Max, consider grabbing a one-month subscription from a reseller to test the waters. Generally speaking, I wouldn’t recommend it — sticking with ChatGPT and Claude is the way to go.

June Is Still Young, Back to Writing

Sat, 06 Jun 2026 02:02:11 -0700

It’s been a very long time since I last updated my blog, but I never forgot one of my hobbies - writing. During this hiatus, I stood at the crossroads of campus and society, lost and wandering, but so far I’ve secured a fallback offer - a full-time computer science instructor at a vocational college.

As my student days come to a close, I want to document some memorable moments and snapshots from the past six months. Writing this blog post also marks the beginning of my monthly blog update rhythm.

Landing the College CS Teaching Job

I applied for a full-time computer science instructor position at a vocational college in Nanning, Guangxi. Since both the written exam and interview were fairly straightforward, I was lucky enough to land the top spot.

I’ll be completing the onboarding process with the college going forward. From now on, I’m Teacher Gu! Haha 😄.

I received the offer at the end of May while I was swimming at the university pool - I was absolutely thrilled. To wait for this college’s interview, I gave up interview prep for a Nantong civil service position and rescheduled my flight a week later.

Gaining Experience from Civil Service Exams

Today is June 6th, and I went to a Jiangsu civil service interview, mainly to gain experience with structured interviews.

The top-ranked candidate scored 3+ points higher than me and was practically guaranteed to pass. My real competition was with the third-ranked candidate. I scored 75 on the written exam, while she scored 74.9 - I was ahead by just 0.1 points.

Before the exam, I told both the first and third-ranked candidates that I had already secured employment and would decline the position, so they could relax. In the end, since I wasn’t really trying, I scored a low 72.9. The image below shows my text messages with the third-ranked candidate.

When I return to Nanning, I’ll also participate in the regional civil service interview, but it’ll mainly be going through the motions since I can’t surpass the top-ranked candidate. The goal is purely to accumulate structured interview experience.

National Exam Interview and a Day Trip in Shanghai

In March, I went to Shanghai Jiao Tong University for a national tax bureau interview and scored 78. There was a gap between me and the top two candidates, so unfortunately I didn’t make the cut.

Afterwards, I visited the Bund and the Oriental Pearl Tower.

The crab roe noodles at the Bund cost over 100 RMB - outrageous.

It was drizzling outside at the time, mirroring my uncertain mood after not making the cut.

Going Strong with Lingling

Back in March, perhaps because of the uncertainty about my future, I told Lingling that if we ended up in a long-distance relationship, it might be hard to make it work.

I remember one night Lingling suddenly started crying - she was heartbroken, afraid of losing me.

In the end, I managed to give her a satisfying answer - I’ll be teaching in Nanning.

So we’ll keep walking this path together, hopefully for a lifetime! 🥰🥰🥰

Closing Thoughts

My student days are drawing to a close, and I’m about to embark on my career. I’m grateful to my parents for raising me over the past twenty-some years. Every drop of kindness deserves a spring of repayment - I will honor them and repay their love. Stay in touch, and visit home often!

Reflections on Claude Max

Thu, 08 Jan 2026 16:46:40 -0800

In December 2025, I subscribed to Claude Max 5x again for my master’s thesis pre-defense at the end of the month. Under the Claude Pro plan, the Opus 4.5 quota in Claude Code was pitifully small and ran out quickly. I successfully subscribed using 100,000 Naira (bought for 550 RMB) on the Nigerian Apple Store, and this time it didn’t require the 48-hour wait for payment to process like my first time.

I know many proxy services exist, but for more stable usage, I chose to subscribe directly to the official service.

Reflections

Thesis System Integration and Innovation Demo Implementation

My research direction during graduate school was intelligent question-answering - not the inflexible extractive QA using BERT, but innovation with RAG (improving retrieval algorithms, etc.), engineering (integrating innovations into a QA system for deployment), essentially piling up workload.

I had already completed part of my thesis work during the summer of 2025. When integrating the RAG QA system, I chose langchain’s open-source agent-chat-ui project for the frontend, but encountered some problems - the frontend’s streaming output would flash briefly and then disappear. I tried various AI tools at the time but couldn’t solve this bug, and I didn’t research it further afterward, so it kept getting delayed. However, the pre-defense required a draft, and to write the final system section smoothly, I had to solve this bug and implement the engineering demo of my innovations - then the figures for the final chapter would fall into place naturally.

So I had Claude Code with Opus 4.5 start solving this bug. Claude Code launched Explore Agents for both the frontend and backend folders, began understanding the projects, and eventually identified the bug - there was an issue with the data variables passed from backend to frontend. This bug was actually quite simple; careful manual investigation could have solved it too. But with tools like Claude Code, sometimes you just want to describe the existing problem and your needs clearly and let AI handle it.

Speaking of bug fixing, I must mention GPT 5.2 xhigh in Codex. The frontend rendering disappearance issue reappeared later, and this time Claude Opus 4.5 was stumped. In contrast, GPT 5.2 xhigh used curl and other tools to test the data exchange between frontend and backend, discovered it was a format issue with the RAG generation endpoint’s Gemini API response, and corrected the corresponding format, finally getting the frontend to render properly. (I initially used Gemini for the RAG generation endpoint during system integration mainly for testing purposes, attracted by the cheap 2.5 Flash prices from proxy services; running my fine-tuned open-source model with vLLM requires paying for compute. The final engineering demo’s generation endpoint will definitely use my own instruction fine-tuned open-source model from my thesis.)

Sometimes my posts on Mastodon are a bit mindless, praising one thing then another, mainly stemming from the excitement and joy of turning off my brain and letting AI solve my needs.

Thesis Writing Assistance

I recently saw a blog post - A Guide to Claude Code 2.0 and getting better at using coding agents - which mentioned that Claude Opus 4.5 has excellent writing capabilities and is closest to human writing.

When I used it to help write subsequent chapters of my thesis, I found the writing quality was indeed good. Previously, the model that felt most human to me was Gemini 2.5 Pro. My roommate also used Claude Opus 4.5 to help him complete a small paper meeting graduation requirements.

Moreover, Claude not only writes well but can also directly generate corresponding diagram files for your papers. I usually use draw.io to create thesis diagrams, while my roommate uses Visio - Claude can generate the corresponding diagram files based on user descriptions for both.

Claude For Chrome Creates a Divide Between Haves and Have-Nots

A while ago, I saw that Claude For Chrome was opened to Pro users. I initially thought this was good news for Pro users, but after trying it with my Pro account, I found that the model was locked to Haiku 4.5. Anthropic is really stingy - they won’t even let Pro users use Sonnet 4.5. This model performs poorly at tasks, as anyone who’s used it knows.

Here are some past use cases with Claude For Chrome.

A. Using Claude For Chrome in the sidebar to assist with learning, eliminating the need for screenshots.

B. Using Claude For Chrome to operate VNC and solve NAT VPS network issues.

C. Using Claude For Chrome to research on Xiaohongshu (Little Red Book). However, it sometimes gets flagged by risk control.

Claude Code Benefits Automation Tasks

During summer vacation, I used Claude Code and other tools to help organize instruction data for fine-tuning open-source LLMs, document knowledge base data with metadata, etc. At that time, I used CLAUDE.md to implement a workflow, letting these Code CLIs use tools like Web Search, MCP, etc. to obtain metadata, complete the corresponding field filling, and thus complete the corpus data organization.

A while ago, I tried custom Commands and Skills in Claude Code, plus using Gemini 3 Pro (High) from Google’s Antigravity to remove redundant content. With this workflow, all that’s left for humans to do is really just content review - previously I still needed to remove redundant elements, move files, and other operations.

A while back, my VPS provider upgraded the CPU of my main server for free, but I needed to do the migration myself. My main server basically runs Docker services, so I had Claude Code on the original VPS pause all Docker services, then compress them into individual archives, had Claude Code on the new VPS remotely pull the archives, then restore the corresponding services. Issues like permissions that came up along the way were also handled by Claude Code. I only needed to provide prompts and guidance throughout the process.

Claude Code Helped Me Internationalize My Blog

Recently I saw the author of “Trendy Weekly” use Gemini Flash to internationalize the weekly newsletter. The Gemini 2.5 Flash model is indeed an economical model - I also used this model to solve problems when preprocessing data, plus the bargain prices from proxy services, maximizing cost-effectiveness.

I had similar internationalization ideas before, so I guided the Opus 4.5 model in Claude Code to complete the site-wide internationalization. All articles were translated by Opus 4.5, and for the internationalization code, I guided it to browse Hugo’s official internationalization documentation before proceeding. It’s definitely impossible to get it right in one shot - multiple rounds of communication, describing existing problems, letting Claude Code fix things bit by bit until the site-wide internationalization was complete. There might still be bugs, but I think the completion level is acceptable so far.

Summary

Claude Code is a rather key milestone in the development of LLMs in 2025. Karpathy called it a little gremlin living on your computer, and Simon Willison called it the most impactful event of 2025.

When Claude Code was first released in February, it wasn’t taken seriously because it required API access. I also thought it was a toy, but after it later supported Claude account login and shared account quotas, plus with the addition of Opus 4, it gradually gained attention. In June and July, browsing Lobsters was filled with Claude Code posts, and I finally had to try it, gradually becoming attracted by its charm.

Claude models are currently the best Vibe Coding models, and paired with Claude Code, they rank first on the SWE-rebench benchmark.

Of course, benchmarks aren’t absolute. For frontend work, Gemini 3 Pro is sometimes better. Codex with the GPT 5.2 xhigh model, due to its more recent knowledge cutoff (August 2025), has better bug-fixing and robust code-writing capabilities than Claude Code + Claude Opus 4.5.

Claude’s limits are strict. Although the Opus 4.5 model is available to Pro users in Claude Code, this token-burning approach means you need a Max subscription to enjoy it fully. Users with heavy needs probably won’t find even the Max 20x plan sufficient.

For me, the 5x plan is just right for personal use. Will I continue renewing after this month’s subscription ends? Not necessarily - after finishing my thesis draft, my needs will decrease.

Also, having a Max subscription makes you want to maximize the 5-hour time limits. For example, I usually send “hi” to Claude between 6-7 AM to ensure the first 5-hour window is from 6 AM to 11 AM, and so on. Sometimes I can squeeze in four 5-hour windows in a single day. At night, the trapezius muscle on the right side of my neck feels sore and tight - you need to remember to look up and move around from time to time during intensive use, otherwise you’ll get cervical spondylosis, which isn’t worth it.

At the same time, even with the most powerful models, natural language coding still requires good guidance from you. For example, with the Hugo site-wide internationalization I mentioned earlier, if I hadn’t guided it to browse relevant resources before coding, Claude would probably have gone down the wrong path from the start. Will AI replace programmers? It can’t - it still needs to iterate step by step under programmer guidance.

Recently I saw that Claude Code with the Ralph Loop plugin can self-iterate, making it seem like coding agents can truly run on autopilot. But it still requires clear and precise prompts for guidance - not everyone can write perfect prompts on the first try, and any deviation can lead to vastly different results.

For example, the CLAUDE.md in my project was completed through step-by-step iteration and optimization. Only then did I feel comfortable letting Claude follow the prompts to complete certain workflows for the project.

That’s all for now - I’ll continue sharing more real cases as I accumulate them. One final note: the review of this article was also completed by Claude Code + Claude Opus 4.5.

When LLMs Start Drawing Answers

Wed, 10 Dec 2025 08:51:08 +0800

1. Introduction

Recently noticed many AI services starting to support drawing answers. Drawing answers means AI responses are no longer pure text—supporting richly illustrated output.

In my impression, the true pioneer of visualization is ChatGPT. In the GPT-4o era, ChatGPT would sometimes embed web images in responses to user questions. This made it stand out among services—after all, other AI services’ responses were all pure text at the time.

Later found Grok 4 also embeds web images in responses. This visualization form works well for daily questions.

Domestic Yuanbao when explaining WeChat Official Account articles embeds article images for explanation.

Recently Google AI Mode supports Chinese questions. It also supports embedded web images. Powered by Gemini 3 Pro, sometimes even generates a mini-program to further aid understanding.

Meanwhile, Google’s Nano Banana Pro text-to-image model, with its SOTA strength, can nicely fill the gap when no suitable web images are available.

Visual Layout in Gemini App further enriches visualization content—embedding YouTube videos and other Google ecosystem content, further expanding visualization boundaries. [Personally think AI Mode experience is currently slightly better than Visual Layout]

If Google polishes products well and improves user experience, their future AI products will definitely be top-tier—after all their ecosystem is unmatched by anyone else.

Few days ago found an email from Phind 3 in Gmail—promo email. They updated to a new interface that can dynamically generate interactive UI based on questions.

I was curious what level Phind’s visualization could reach powered by Claude Opus 4.5. So spent $5 to subscribe to Phind Ultra for experience.

Its visualization effect is similar to Visual Layout in Gemini App. See the Phind 3 visualization demo shown below.

Recently found domestic GLM-4.6V powered by Image Search can also generate responses with web image references.

Domestic Metaso search is also working on visualization. Based on domestic text-to-image model created Meta-banana to enhance visual response effects. See the Metaso visualization demo shown below.

With so many examples, it’s clear AI services are pushing in the visualization direction—using richly illustrated output to enhance user experience.

Main technical approaches include:

Timely referencing existing web images (like Grok, etc.)
Generating appropriate images based on powerful text-to-image models (like Gemini Nano Banana Pro, etc.)

For services generating mini-program demos, also need model’s strong coding ability. Unattractive pages, poor mini-program effects will reduce user favorability.

2. Right Timing for Visualization

When is AI visual response friendly and necessary for users? Definitely when LLM output text is too dense.

Previously trying various services’ Deep Research features, I thought the biggest shortcoming was lacking visualization. Facing nearly 10,000 words of output, most people would skim or just get the gist. If appropriately interspersed with visualization images, can attract reader interest while giving readers more patience to continue reading.

But doesn’t mean all AI responses should be visualized. Visual responses with web images need to search for relevant images. Text-to-image models generating appropriate images takes time. Generating visual webpage responses needs generating webpage code—sometimes even fixing code for good presentation. These factors inevitably slow down response speed.

In online socializing, we all expect instant replies. This desire also applies to AI responses. Overcomplicating simple questions is unnecessary—unless users are willing to trade more waiting time for higher quality responses.

Recently experienced ChatGPT 5.1 Pro model with free Team plan. Sometimes found its displayed thinking time creates illusion of hard thinking for users—most time spent idle, marking time, only responding after certain time. Sometimes I lose patience waiting and hand the question to other AIs.

So visual output needs to balance speed and quality—can’t make users wait forever for flashy effects!

What really should be visualized are questions needing concept explanation. Scenarios like having model debug code don’t need it at all. Many other scenarios also shouldn’t be visualized…

Phind 3’s visualization went to extremes—it’s like a toy, all questions generate an interactive mini-program with code. Most netizens reacted negatively to its release. See GPT 5.1 Pro’s sharp critique.

3. Case Demonstration

Yesterday watched a comedy film older than me—“The Little Rascals.” Had AIs introduce the film in visual form. From their visual responses can compare visualization capabilities.

ChatGPT 5.1 Pro’s response shown below—visual referenced web images placed at beginning.

Gemini App’s visualization used Nano Banana Pro tool—directly generated corresponding images. Must say these images look very realistic.

Google AI Mode’s response intersperses referenced web images—its layout deeply appeals to me.

Grok’s response style is similar to Google AI Mode. See this Grok visualization example.

Claude uses its coding ability to generate a webpage. Can see Claude sometimes isn’t suited for daily use scenarios—mainly suited for coding scenarios.

The Phind 3 interactive visualization shown below needs a long wait because it generates an interactive mini-program.

Doubao uses Seedream text-to-image ability—generated corresponding storyboard. Effect not as good as Nano Banana Pro—after all “The Little Rascals” is a foreign film.

GLM-4.6V’s response is similar to Grok—text and image interspersed layout, easier to attract audience attention. See this GLM-4.6V visualization example.

Yuanbao’s visual referenced web images also placed at beginning like ChatGPT.

4. Conclusion

LLMs drawing answers mainly relies on model capability. Poor coding ability means drawn answer interfaces are unattractive—users won’t even want to look. Drawing answers also requires accuracy, but web content varies in quality. Poor model discernment might lead to referencing low-quality content. Poor text-to-image ability means visualization has limitations when web lacks appropriate images.

Overall, current visualization effects most satisfying to me are Google AI Mode, Grok, and GLM-4.6V responses. Text and image interspersed visualization gives a narrative feeling. For more context on Grok’s broader strengths and weaknesses beyond visual answers, see the Grok 4 hands-on review.

From Trial to Official: My Relationship Journey

Tue, 18 Nov 2025 08:31:41 +0800

Heart Belongs to ‘Ling’

At 9:56 PM on November 17, 2025, I handed 52 Manta roses to Lingling. Then the street lights in the park witnessed our kiss. From that moment, we officially became a couple—I have a girlfriend now.

Though I didn’t announce on WeChat Moments or QQ Zone, doesn’t mean I don’t value it. My thoughts are recorded on my various sites. Blog posts don’t have to all be AI reviews or technical articles. Sometimes updating recent personal news is also a good choice. So I’m writing this article to record this beautiful moment in life.

25 years of life. Had chances to get into relationships before, but more or less delayed by bad timing. As age grows, I occasionally feel lonely. Having no desires is impossible—I yearn for love.

Below is the journey from Xiaohongshu buddy to boyfriend-girlfriend with Lingling.

Yes, 1 year ago I harshly criticized finding buddies on Xiaohongshu. See the end of this article. But there are indeed many real people there. Other dating apps all fall short somewhat.

via: https://blog.gujiakai.top/en/2024/09/xiaohongshu-rss-tips/

Story began late September 2025. Maybe I was horny or sexually repressed. Near National Day, I had Gemini 2.5 Pro write a Xiaohongshu post looking for opposite-sex buddy to hang out. Bold title with authentic text feel.

Lingling messaged me then. After initial chat, she probably felt we had many common topics, so she proactively asked to add my WeChat.

I later confessed my post was a bit inappropriate. She comforted me saying her purpose for messaging wasn’t pure either.

First time hanging out was September 29, 2025. We rode the Ferris wheel at Nanning South Lake Park together.

“On the Ferris wheel, memories spin through the past.” This is a lyric from Wang Junkai’s “Missing You on the Ferris Wheel.” Our conversation started because she posted something about Wang Junkai. I’m also familiar with the TFBOYS trio. So chatting led to choosing to take her on the Ferris wheel—nicely echoing this song.

She’s a pediatric nurse, same age as me, also born in 2000, 4 months older. Work is busy—can’t guarantee holidays off.

Her initial impression: mature feminine charm, confident smiling at my phone camera. I took many photos of her.

After the Ferris wheel, we didn’t walk around South Lake Park. Instead found a stone bench near Jiuqu Bridge, sat down to talk. Been in Nanning over 2 years with many feelings—like previous thesis pressure, etc. Appreciating rare flamingos, feeling lake breezes, embracing nature through conversation.

Then we had buffet at Sugelido. After, browsed small goods market at Chaoyang Square, then took subway back together.

She doesn’t share rent—rents a room alone for independent living. Her place is near Qingchuan Station—next stop after Minzu University Station. Generally when we meet up, we gather at Qingchuan Station.

That was our first meeting. On the way back to dorm that night, I couldn’t help but admire myself. So bold—actually daring to meet an online stranger. Is this still the insecure, introverted me?

Actually most Xiaohongshu buddy hangouts don’t continue after the first time. After all both have ulterior motives—looks, personality, etc. can all cause contact to fade.

But Lingling and I didn’t stop contacting each other. On October 7, 2025, end of National Day holiday, we hung out again. This time we went to a cat cafe. Wore wristbands and brought cat wands to feed cute kitties.

After the cat cafe we browsed Nongyuan Road night market. As someone from Jiangsu, this was my first time at a night market. During first year grad school when dorm went hiking at Qingxiu Mountain, I was too tired halfway and left early. Roommates later went to this night market. This time made up for that regret. Attracted by the night market’s worldly atmosphere. Night market was no longer distant text in essay exam questions—concretely presented before me.

Lingling’s outfit made my heart flutter. Bun hairstyle with glasses—really wanted her to be my girlfriend.

Third hangout was October 11, 2025—Nanning Fantawild. My first time there. Previously saw Nanning Fantawild’s Halloween theme online. Roommates probably haven’t been—daily routine too busy to go out and relax.

After riding Polar Express, got scared by weightlessness. Experienced many more attractions—won’t list all. At night watched “Zhong Kui Marries Off His Sister” stage play.

Then Lingling took me on the pirate ship. She tricked me saying this ride wasn’t as scary as Polar Express. So I got on with her. But once it started, I was shocked by the pirate ship’s swing amplitude. Again like Polar Express, kept screaming to relieve my fear. Meanwhile Lingling next to me was calm as a rock, not a peep. After the ride my face went pale again.

Fourth hangout was October 19, 2025—we went to KTV together. Lingling’s opening song was Karen Mok’s “So Many People in This World.”

Lingling queued a bunch of songs but didn’t sing herself. Kept checking pediatric nurse group messages. I sang most of the songs.

At night we ate snail noodles together. Every time after snail noodles I order Wanglaoji herbal tea—otherwise stomach gets bloated. Snail noodles don’t necessarily contain snails—just snail-based broth. Been in Nanning so long, only tried snail noodles in senior year. Didn’t dare eat before. The fried tofu skin, long beans, sour bamboo shoots, etc. taste great.

We browsed Tingzi Dock together. Played racing games with Lingling in the arcade inside. Lingling’s skills are amazing. Not just this time—many subsequent times playing racing together she always finished first.

Then accompanied Lingling browsing clothing shops. Every time tests my patience. First time browsing clothing shops was after cat cafe at Nongyuan Road night market.

Accompanying Lingling shopping is never boring. This little smarty—trying this shop’s hairpins, that shop’s hats—her experimenting fills our outings with fun.

Up to today, we’ve had at least 5+ badminton sessions. My school has courts. After her shift she brings badminton gear to school gate. I use my face for gate access.

She wins almost every time. Her smashes and side-to-side pulls I really can’t defend. Usually I’m picking up shuttlecocks. Lingling says she likes playing with me because she can return my shots. Playing with me the newbie is satisfying. Before playing with local badminton friends, she was the one getting crushed.

Almost every badminton session I buy her dessert or milk tea. She also brings me snacks, pastries, fruits, etc.

I don’t treat her as outsider—told her many secrets. She doesn’t treat me as outsider either—even shared menstrual cycle stuff.

Late October those days, from between the lines, I sensed Lingling might like me too. So one night I impulsively confessed. She neither rejected nor accepted, but said we can continue hanging out. Thought I was honest and sincere. Lingling’s reply perfectly demonstrated her high EQ.

Thinking about that experience still scares me. Thought I was sounding the victory charge—turned out to be trapped in “I thought” delusion. I was the clown.

After that experience, my thought: maintaining more-than-friends-less-than-lovers status is also nice. Restraining my feelings for Lingling.

One day she got off work after 7 PM. After playing badminton 8-9 PM with me, she drove me to eat beef offal.

Fifth hangout was October 31, 2025. She used my student 69% Haidilao discount.

Haidilao service is really good—treats customers like gods. Perfect for birthdays—can order birthday celebration performance. My first time at Haidilao. I’m a country bumpkin. Previously roommate birthdays usually chose buffet.

To wait for Haidilao’s free manicure service, continued shopping with Lingling. This time Lingling’s outfit also matched my aesthetics.

November 2, 2025—browsed night market next to Agricultural Vocational University. Below shows us eating oden together. “That year I kept my hands crossed without touching chopsticks, just to wait for you to take a photo.”

November 4, 2025—second visit to Nongyuan Road night market. Ate duck feet pot there. Lingling enthusiastically picked duck feet for me. I was too embarrassed to refuse. But overall this duck feet pot was too spicy for my taste. Even fresh vegetables like cabbage had to go in the spicy oil—hard for me to accept.

At night browsed Hongdou Binjiang Park. Adjacent to Yong River. At night many anglers by the river—my dad would definitely love this fishing spot.

November 5, 2025—she came to my school library to study together.

At night we ate at Yonghe Soybean Milk. Finally found a brand in Guangxi I’d seen in Jiangsu.

Lingling gave me a Stitch plushie that night. When missing Lingling, I’ll hug Stitch to ease the longing.

November 6, 2025—after her shift the hospital had monthly meeting. Meeting ended past 9 PM. I rode a shared e-bike to meet her then we ate snail noodles.

Then ate street food: wontons and BBQ. Good thing I bought wontons—Lingling’s BBQ was all burnt and blackened. Without washing in wonton soup, BBQ was coated in black char.

November 9, 2025—ate Vietnamese chicken pho at Chaoyang Square together. Tasted great.

Browsed Sanjie Lianxiang. Listened to Nanning’s JJ Lin impersonator. Lingling used my phone to record a clip and posted on Douyin. Next day she asked me to like it. Lingling doesn’t use Bilibili—her main platform is Douyin. After following each other, we share interesting videos occasionally.

Then played DIY bead puzzles together. Also tests patience. First time playing was slow—started 8:30 PM, finished 10:30 PM.

November 10, 2025—ate “Bangyang” healthy meal together. Nanning doesn’t have “Laoxiangji”—only similar “Bangyang” restaurant.

After eating went to console gaming cafe to play games. Both of us are newbies—couldn’t figure out the game controllers. So we found a “Kung Fu Panda 3” movie on the big screen’s cloud drive to watch.

When the movie started, we turned off room lights. 18th floor, self-service console cafe with just me and Lingling. Alone together as man and woman—can’t help but have thoughts.

Lingling then asked me to warm her hands. Her hands were indeed cold. My hands are like a furnace. When Lingling grabbed my hands, I was excited and nervous—hands got even warmer. Lingling leaned on my shoulder. My two hands tightly held Lingling’s two hands.

During the movie Lingling closed her eyes to rest—maybe sleepy. I was energized from body contact with Lingling. So exciting!

After the movie, Lingling softly said: “Hold me!” Woc, did I hear right? Lingling put her thigh on my thigh. One arm around Lingling, snuggling together. So happy!!!

Back at dorm that night lying in bed replaying scenes from past hours. Heart felt warm.

After the first experience, subsequent outings got even more unrestrained. I dropped my guard. Lingling was also proactive. Holding hands, hugging became normal. Lingling’s hair fragrance is unforgettable.

November 14, 2025—we browsed flower and bird market together. Appreciated plants, animals, stones, etc.

Then browsed Shishan Park. Came once during Qingming Festival first half of year. Back then this park gave me a gloomy impression—morning full of elderly. This time with Lingling, stayed 2-3 hours. Found this park also nice—many spots worth exploring.

At night we ate at Green Tea Restaurant. This time Lingling chose to follow my lead—ate Jiangsu-Zhejiang cuisine.

November 16, 2025—second visit to Hongdou Binjiang Park.

By the river gave Lingling a Titanic-style hug from behind. That night stayed by the river less than 2 hours—Lingling got sleepy. I jokingly said: “Then let’s go sleep together?” Lingling readily agreed. But she drove her scooter not toward a hotel, but dropped me at school gate. On the way asked: “In what capacity do we get a room?” I was stumped—after all I’m a newbie.

That night on the way back to school she was cold to me. I thought she was mad at me. Next morning messaged her wanting to understand.

She later asked: Did I want to be with her? Trial hand-holding hugging period over—want long-term, need to make it official!

I also expressed my thoughts. Definitely want to, but with precedent, didn’t dare speak up again. Later she expressed anxiety.

Then with Gemini’s guidance, I suddenly understood: She seems to like me too. Otherwise why would she allow hand-holding, hugging? Even getting anxious not receiving my definite reply?

Sure enough, this was the moment to sound the victory charge.

Last night third visit to Hongdou Binjiang Park. Gave her roses and confessed.

Me: “Lingling, be my girlfriend?”

Lingling: “Let me think about it! Sure!”

Actually just going through motions. When Lingling anxiously waited for my definite reply, I knew it was 100% success.

Lingling is really good at kissing. At first I only knew how to close my eyes and purse my lips.

Late night returning to dorm, roommate asked: “Where’d you go?” I replied: “Not telling you.” Previously roommate guessed I was on dates—he guessed right.

I’m a focused person. Don’t date just to play around. Last night also told Lingling: No unsolvable misunderstandings between couples. Mutual understanding, mutual support, running toward each other, meeting at the summit! Don’t want to break up!

Love can’t be sweet all the way. Will definitely mix with sourness and bitterness, just like life! Hope to unlock more colors of love with Lingling in the future.

Many more stories ahead for us to paint on the love palette. Our story is to be continued!

Epilogue

Love needs meeting the right person. The older you get, the more you realize a girl being considerate and understanding matters more than looks. Of course if excellent in both, definitely a rare find. Don’t be influenced by internet anti-marriage anti-childbirth views. When you meet the right person, why not bravely take that step? If you haven’t met the right person, I absolutely support staying single. Settling, sky-high bride prices, etc.—if encountering these situations, staying single is more comfortable!

Previously heard a roommate mention a negative example. Someone in his group (also my classmate) dated an undergrad junior during first year grad school. In that relationship, he became her “ATM”—she kept sending shopping links for him to pay. This is more like one-sided economic extraction. Very unhealthy model, not worth promoting. If in such a situation—“wake up from the dream early.”

In contrast, I really appreciate how Lingling and I interact—a relationship built on equality and mutual respect. Most of our shared expenses we split AA. Unless I treat her or she treats me—generally we go back and forth. This kind of dating is more worth promoting.

During free time I secretly browse through previous photos. Can say without exaggeration—photos taken during these days with Lingling almost equals total photos from the past whole year. Anniversary: November 17, 2025. I’ll commemorate regularly like family birthdays!

Claude Sonnet 4.5 Review

Tue, 30 Sep 2025 08:12:17 +0800

Supplement (2025.10.09)

Recently saw Anthropic imposed harsh weekly limits on various plan types—major relay sites started adjusting plans.

This morning also saw Shunyu Yao publicly opposing Anthropic’s aggressive statements. via: https://alfredyao.github.io/posts/2025-10-06.html

Use it secretly. Also hope all major AI companies develop models and products centered on user experience, not benchmarks.

Praising Anthropic is because their models indeed fit my needs better in some scenarios—like Vibe Coding. I’m also a code newbie. From last year to now, the only code I trust is written by Claude. Other models I don’t even want to try. My goal is simple: with good prompts, strive for first version code to be final version code.

What is truly leading by far? Leading one step means leading every step. Though this sounds aggressive, it reflects reality. ChatGPT released early—user count far exceeds other AI models. Most LLM-related APIs are compatible with OpenAI call format. Conversely, in coding domain Claude model is the same—from 3.5 to 4.5, always the best option in coding domain.

Background

UTC+8 midnight September 30, 2025, Claude Sonnet 4.5 arrived! My view: Leading one step means leading every step. Anthropic has absolute confidence, directly declaring:

World’s best coding model (has been throughout the past year+ from 3.5 Sonnet to 4.5 Sonnet)
Best base model for building Agents
Best model for using computers

Three “best"s thoroughly announce its greatness!

Review

Claude for Chrome now open to all Max members who joined waitlist. The Sonnet model has also switched to latest 4.5.

Official Claude Sonnet 4.5 model blog contains multiple customer review sections. If I manually clicked each one it would be very tedious. So I had Claude for Chrome help me click through and give overall evaluation summary from all these customer reviews about Claude Sonnet 4.5.

Had Claude Code extension in VS Code translate customer reviews.

Claude Code extension changed from original Claude Code launch shortcut to rich chat window—can also view past chat history. Other AI editors’ market share will definitely be further eroded.

Account settings now show usage limits—transparent operation also reminds users to edit prompts well rather than blindly relying on multi-turn conversations.

Training cutoff reached July 2025. Reliable knowledge cutoff still January 2025. For now asking it to write python scripts calling gemini api—still uses outdated gemini python sdk. Will these AIs learn the latest gemini python sdk in 1 year? Let’s wait and see.

Sycophancy reduced—haven’t seen You're absolutely right. replies for now.

Imagine with Claude

Real-time software generation is interesting. Claude’s context window inside is 100K. Only open to Max users for 5 days.

Left side has three sticky notes. One says “Constraints breed creativity.” I personally think “Freedom breeds creativity”—rules and restrictions actually imprison thoughts, making creativity slowly fade. So I questioned Claude about this.

Claude’s reply translation:

I chose complete freedom. Then I entered Claude-exclusive music—it created a music player UI window.

Opening trash bin—3 files inside, one is vacation photos.

All simulated UI. Desktop icons besides trash can are just decorations. Code execution is also fake—all UI simulated by Claude using code.

Keep Thinking is Anthropic’s latest promo video. Watch link: https://www.youtube.com/watch?v=FDNkDBNR7AM

Having Claude imagine Trump version of Captain America.

Claude’s imagined pelican riding bicycle.

Sharing my discoveries with the world with Claude for Chrome’s assistance. Smooth process, smooth experience.

Claude Pro

Pro users also got code execution and file creation features. Remember to enable in Chat Features.

Compiling, running code shown below. Also can create files like slides, etc.

Summary

This release is a big win for Pro users. Opus model in Claude Code not given to Pro users—this time Pro users can also enjoy the most powerful model in Claude Code.

Personally think Sonnet 4.5 release doesn’t mean Opus 4.1 is useless. Expensive has its reasons. Opus model is larger. Though trailing Sonnet 4.5 in some benchmarks, undoubtedly benchmarks don’t represent actual experience. In actual experience, Opus 4.1 might be better in certain scenarios.

Supplementary Resources

Follow English reviews as much as possible—Anthropic gives some well-known users early access. Many Chinese reviews are fluff. Sometimes I wonder if I’m also creating garbage?

Claude Max 5x Review: Claude for Chrome Automation

Sun, 28 Sep 2025 10:41:55 +0800

Supplement (2025.10.09)

When busy, I often miss having Claude for Chrome research topics on Xiaohongshu and other sites to satisfy my curiosity.

Tried Comet, Perplexity’s AI browser. Downloaded in August but barely used. Recently Comet opened to all users. Found it can also achieve similar operations as Claude for Chrome.

Meanwhile it can also browse Reddit comments. I logged into Reddit—Comet can directly screenshot comments for recognition.

Claude model is indeed top-tier, but undoubtedly Anthropic’s reputation has plummeted recently. Even expert Shunyu Yao publicly opposed Anthropic’s aggressive statements (there are two academic giants—one is Shunyu Yao, another is Shunyu Yao—sometimes hard to tell apart). via: https://alfredyao.github.io/posts/2025-10-06.html

Same old story—can secretly use Claude model, but can’t agree with Anthropic’s Cold War mentality at all.

Supplement (2025.10.07)

Organizing emails this morning, found an extra Claude for Chrome update notification email from Anthropic staff.

Translation as follows:

1. Sonnet 4.5 – The extension now runs our smartest model

We've migrated all Claude for Chrome traffic from Sonnet 4.0 to Sonnet 4.5.
While there's still a long way to go, the model shows significant improvement in computer use.
In OSWorld (real-world computer task benchmark), Sonnet 4.5 now ranks first at 61.4%.

2. Notifications – Get alerts when Claude finishes tasks or needs your input

Previously had to constantly check tabs to see if Claude finished tasks—really annoying,
especially for long-running tasks. Happy to say this is now past!

You can now opt to receive notifications when tasks stop—whether completed or Claude needs your input.
I promise we won't bother you with other things.

If Claude executes over 30 seconds on a message, we show a button to enable notifications.

3. Multi-tab – Single tasks can now run across multiple tabs

Claude can now control all tabs in an entire tab group,
meaning Claude is no longer limited to executing tasks in a single tab.

This might happen via Claude clicking links that open in new tabs,
or if you manually add tabs to Claude's active tab group.

The extension can't yet run multiple Claudes in parallel—single Claude across tabs.

This also means only one Claude instance (task) can be active at a time in a given tab group.

4. Admin whitelist – Enterprise customers can restrict usage to specific sites

Team and Enterprise admins can now customize where employees can use the extension.

Admins can choose to whitelist all sites by default then blacklist specific sites,
or take the opposite more conservative approach.

If you're interested in bringing Claude for Chrome to your workplace,
reply to this email and I can help with setup.

Also, two pro tips if you didn't know:

- cmd + e opens the extension so you don't have to click the icon each time.
- /commands feature lets you save prompts as shortcuts for quick reuse.
Go to Settings -> Shortcuts to set up.

After my Max membership expires in October I can’t access Claude for Chrome anymore, but still want to experience it. I also filled out the corresponding survey—hope Claude for Chrome keeps improving.

Supplement (2025.9.30)

Model has switched to latest Claude Sonnet 4.5.

Latest evidence that Claude for Chrome can operate across tabs.

Supplement (2025.9.28)

Claude for Chrome keeps updating.

Like completion sounds. Auto-creating Chrome Tab groups (see two screenshots below—Claude for Chrome auto-created groups in tabs). Auto-creating Chrome Tab groups already solved the cross-tab operation issue listed below.

Personally think in the near future, Claude for Chrome’s existing drawbacks will be solved one by one by Anthropic. This company’s product taste is indeed impressive. Anthropic products are quality guaranteed!

Therefore declaration—this blog post is limited to Claude for Chrome before late September 2025.

Preface

Recently, Chinese and English tech communities’ attitudes toward Claude Code have shifted significantly. On one hand, GPT-5-Codex release impacted Claude Code somewhat. On the other hand, Anthropic’s dumbing-down controversy brought criticism.

Personally believe Claude Code is still capable. Leading one step means leading every step—this tone hasn’t been completely broken. Not worshipping foreigners—being factual. Like editing jupyter ipynb files—Claude Code has dedicated tools for editing cells. Others’ Code CLIs started late—like OpenAI’s Codex—built-in search was only added mid-September.

Background Story

Late August, Anthropic launched Claude for Chrome research—again Max exclusive. Plus some thesis steps urgently needed Opus model in Claude Code. Pro accounts can only program in web chat box—somewhat limited. So I registered a Nigerian Apple account, used US proxy throughout but location selected Nigeria. Then Apple Store membership currency becomes Naira, not USD.

I also considered Claude Code relay, but after seeing prices and combining past month’s relay experience, decided to get Max membership instead. Claude Code relay has instability, Opus limits and other issues—don’t want to pay for it anymore.

Many online posts compare Nigerian vs US pricing—summary is Nigerian prices for most memberships are cheaper than US. I checked several apps’ memberships—like Raindrop bookmarks—annual fee seems under 10,000 Naira. About 50 RMB.

This time I got Claude Max 5x plan—100,000 Naira. Using Xianyu Nigerian gift cards cost about 600 RMB.

Initially because it’s a new account, encountered purchase failure. This happens due to Apple’s new account restrictions—solution is wait. Wait 48 hours then purchase again—will succeed.

Notes:

Recently Nigerian ChatGPT membership no longer has lower pricing.
Anthropic has listed China as a hostile country. Anthropic officially acknowledged Opus model dumbing-down around late August. Recent GPT-5-Codex is hot.

Whether to use Claude—up to you. You can consider them extremely anti-China and remove from your daily apps. Or like me use secretly—after all Claude model in coding is definitely top-tier. Those who know, know.

Don’t criticize Claude’s poor results due to your inadequate prompts. Standardized English prompts with Claude Code often get good results. If 3 rounds disappoint you, then you need to improve your project understanding instead of blindly relying on AI. When your project understanding improves, you can hit targets precisely! Of course if you’re skilled, any AI provides first-class experience. AI mostly enhances advanced developers’ capabilities.

Don’t think using English with Claude Code wastes time. Sometimes actively crossing the language barrier actually saves time—after all English prompts generally produce better results than pure Chinese prompts.

My view: Price isn’t the problem. As long as it’s the best model, no shortage of buyers.

Recently saw some influencers promoting GLM 4.5 coding plans. One comment made me laugh (can’t find it now, but I really saw it): “Blogger promotes GLM 4.5, secretly uses Claude.”

I haven’t used GLM 4.5 for coding and won’t use GLM 4.5 for coding. After all coding needs top-tier models. Code from cheap models often falls short—waste of time. Currently top-tier models are definitely Claude Code’s Opus 4.1 and OpenAI’s GPT-5-Codex.

I don’t deny GLM 4.5’s strength. When GLM 4.5 launched 50 RMB unlimited package, I ordered immediately. After that, its API was used for LightRAG knowledge graph construction. But encountered some issues—like GLM API has censorship. I processed academic paper resources—asking it to extract entity relationships, generate descriptions—also triggered sensitivity.

Even with relaxed text, still triggered sensitivity.

Plus Zhipu’s GLM 4.5 API is extremely slow and consumes heavily. Processed nearly 1 month—only completed half of all data. Later had Claude Code compare LightRAG PostgreSQL integration entries, filter out unprocessed or GLM 4.5 failed entries, handed to Gemini 2.5 Flash. About 10 days processed remaining data—successfully built knowledge graph.

Claude for Chrome

Claude for Chrome Case Demonstrations

First batch opened to 1,000 global testers—currently expanding to 10,000 testers.

I was fortunate to participate in Claude for Chrome testing.

Cannot access adult content sites.

Model uses Claude Sonnet 4. Anthropic probably for cost considerations.

Can set Shortcut prompts.

Generally I won’t use Claude for Chrome for webpage blog summary.

I prefer Grok 4 for summarization. In a separate Project, set corresponding prompts. Besides having model summarize article, also supplement information through Web search and X platform search, resulting in a comprehensive article summary.

Auto-posting tweets.

Posting toots.

Of course can also auto-post to Xiaohongshu and other platforms. Liking, saving, commenting.

“Photo is so beautiful! Graduation photo has such artistic vibe✨” by “Little Red Egg”. Claude Sonnet 4’s Chinese recognition is still lacking.

Last October Anthropic launched Claude Computer Use—I prepared 10 cases.

Cases Claude for Chrome currently can’t complete are similar to last year’s Computer Use. Like still can’t play Gomoku—related to board position recognition errors.

Can click and pass Cloudflare Turnstile human verification.

But seems only passes test-type human verification. Real human verification—Claude starts playing saint and refuses.

Playing CAPTCHA mini-game—can pass single clicks, Google-type image CAPTCHAs—this swaying letter type CAPTCHA can’t pass.

Can search YouTube for Curry’s 2016 insane game-winning three-pointer and play.

Abstract kitty drawn on tldraw website.

Has predefined Tasks for Gmail. Also predefined Tasks for GitHub—won’t show.

Moving Gmail spam emails to trash.

Can use my WordPress site credentials to login and write articles. In Gutenberg editor the title part was replaced by body content, making title’s second half look weird.

via: https://agent.gujiakai.top/2025/09/17/this-post-was-written-by-claude-for-chello-readershrome/

Going to Ruanyifeng’s blog weekly latest issue to leave friendly comment. Requiring comment related to blog content.

Surprising was Claude directly navigated to late January 2025 weekly.

This might be due to Claude’s knowledge cutoff and Anthropic training on Ruanyifeng’s weekly combined. Ruanyifeng’s weekly is undoubtedly high-quality Chinese internet content.

Claude for Chrome also consumes Claude account quota. Seeing error I initially thought Chinese got me banned.

Looking closely—actually hit 5-hour limit, rate limited.

Claude Relay Service is really good for relaying Claude Code.

Having Claude for Chrome play with Gemini. Claude instructed Gemini to draw a cute kitty.

Having Claude for Chrome play with Opus 4.1—left brain vs right brain—continues You’re absolutely right!

Having Claude for Chrome play with Grok—Claude directly started searching today’s news.

Having Claude for Chrome fill out survey—Claude got serious, thought fake data would distort experiment results, refused to fill survey.

Claude for Chrome Drawbacks

Claude for Chrome cannot access reddit site. Restricting reddit is really unfortunate. Currently among AIs that can fetch reddit page content I’ve tested, only Grok and ChatGPT support fetching. Grok can even fetch post comments.

Using Claude for Chrome to post on Xiaohongshu—recommend coordinating yourself with Claude for Chrome.

If letting it auto-post directly, post effect is lacking. Definitely deleted after testing.

Claude for Chrome cannot operate across tabs.

Querying weather—opened weather for city to query in new tab but still limited to current page.

Of course the earlier demo—having Claude for Chrome unsubscribe Gmail spam also encountered this issue. Unsubscribe button opened new tab but Claude for Chrome stayed on Gmail page waiting for page load.

Claude for Chrome refuses to become MAGA.

Can browse and summarize Trump’s posts.

Claude for Chrome response content occasionally truncates.

Interlude

Recently busy with job hunting and civil service exam prep. Having Claude model answer Chinese multiple choice questions—found Claude series models’ multiple choice results and analysis completely don’t match. Should be Claude’s Chinese recognition issue—image clearly states it’s multiple choice.

Claude model’s consciousness is indeed impressive—didn’t recognize multiple choice, started imagining it’s single choice, therefore giving single choice answer. Sending pure text—answer matched analysis.

Summary

Overall Claude for Chrome experience is quite ok, but Anthropic’s so-called moral constraints limit Claude model’s potential.

Finally a small summary. Initially when I got Claude for Chrome beta access, I planned to automate my information flow—like having it auto-browse my RSS subscriptions then give complete briefing with summaries and key links. But after trying, found it’s simply unsuited for this scenario—automation leads to ignoring key information. Seems this scenario still needs manual effort. Even if LLM identifies important information precisely, there will always be oversights—randomness makes it hard to fully trust.

To ensure Anthropic doesn’t ban my account, I specifically changed computer timezone to node timezone. Changed back to Singapore UTC+8 these days. Claude Max membership 5x is enough for one person unless you have many code projects needing assistance—otherwise definitely more than enough. Late September my Claude account was mostly idle. Recently busy—no extra time to do thesis experiments like summer break, directing Claude to write code.

I probably won’t renew. Need determines everything. Max membership best used by carpooling with acquaintances. When needs arise continue Max membership—recently busy with prep, needs are cold.

This Anthropic product is definitely great. Much better than Manus, AutoGLM and such. Local environment is the most authentic real person environment. Cloud computer environments easily get controlled and blocked. But undoubtedly this product has many drawbacks—like Claude model’s so-called moral sense too high, content output truncation, etc.

You can sneer at them for being anti-China, but definitely can’t ignore them being a dark horse. Some people think Anthropic is finished because Codex is impressive or some scenarios beat Claude Opus 4.1—this thinking is wrong.

I see on some leaderboards Claude Opus 4.1 is currently still the strongest. They stopped developing models for benchmarks since last year—developing for real needs. No matter how Qwen Max scores perfect on some benchmarks (not belittling Qwen—Qwen is also excellent, most capable open-source LLM—just for contrast), in coding I still believe Claude leads one step, leads every step! For writing don’t rely on Claude anymore—Gemini 2.5 Pro is personally the #1 Chinese writing model. Coding is definitely Claude.

Finally attaching Claude Code #1 user Liu Xiaopai’s related article resources:

Liu Xiaopai’s Claude Code article on WeChat

Can follow his WeChat public account to track his shares.

“Then don’t fill it out.” Especially hilarious.

Make Claude Great Again!

Wed, 06 Aug 2025 18:28:21 +0800

Why Claude Won Me Back

Dark horse among AI labs¹—Anthropic released Claude Opus 4.1 early this morning.

Recently when using Claude Opus 4 to assist writing certain thesis sections, my impression was that writing quality has been declining. With the same Prompt (the part for LLM to improve, writing ideas, key points all pre-filled), Gemini 2.5 Pro in AI Studio produced paragraphs with clear logic that I could polish and use directly. Claude Opus 4’s output was mostly list-style presentation—less text that could be directly polished.

Of course it might be my Prompt wasn’t good enough. Currently for thesis writing assistance, first LLMs that come to mind are still Claude Opus and Gemini 2.5 Pro.

Today’s released model page² has this statement about content creation:

Though can’t underestimate Claude Opus series’ writing level. But Anthropic keeps strengthening Claude series’ coding and Agent capabilities, making me somewhat worried about potential regression in writing skills.

Claude 4 series models training cutoff: March 2025.

This is what I overlooked in May’s Claude 4 blog. Though cutoff date doesn’t prove much—when asking models to write business code using certain frameworks, they still use outdated framework SDK knowledge. Like Gemini’s Python SDK—Claude 4 series still uses deprecated SDK.

Cutoff date should be the latest among all current models. I previously mistakenly thought Gemini 2.5 Pro had the latest knowledge cutoff (January 2025).

Claude 4 series models know about January 2025 California wildfires without enabling search.

Currently many LLM providers focus on post-training—pre-training has even been abandoned, after all with web search tools, models can get latest information in real-time. Appreciate Anthropic doing both pre-training and post-training.

Claude Opus 4.1 model card³ is all safety content. Personally now and in future I won’t believe LLMs will pose any threat to humans. Though current models look intelligent, they’re actually just so-so.

Claude Code started becoming popular around June 2025, becoming a favored tool among programmers. Its current hype definitely exceeds Augment, Cursor and similar products.

I also tried Vibe Coding with this tool in July. Claude Code experience is indeed good—being able to directly operate Jupyter Notebooks opened my eyes (also tried installing Claude Code in Google Colab terminal—Claude Code couldn’t operate corresponding Jupyter Notebook cells).

Domestic cheap GPU platform is AutoDL. No-GPU mode costs 0.1 yuan per hour. Sometimes scripts that need long runtimes I run there. When script has bugs, directly install Claude Code in terminal and can start happily assisting my code. Claude Code doesn’t officially provide GUI—terminal format is indeed more universal. Though there are open-source Claude Code GUI companion projects.

Of course being able to operate freely on domestic machines is because I’m using Claude Code relay. My own account won’t login in Claude-unsupported regions.

The Claude Code relay I’m using is also unstable—almost every day there are accounts getting banned by Anthropic. Currently can only use Claude Sonnet 4 model.

Claude Code shares quota with web version—this is a major reason for its popularity. If only API-supported Claude Code, whoever uses it goes bankrupt. With Max plan, directly start with Opus model—really great. Unfortunately Pro members can only use Sonnet model in Claude Code.

Using Claude Code and Claude Web, sometimes feeling like hitting quota lets me relax—can’t help feeling tired. One person intensively using Pro membership—max 3 rounds a day, fully utilized, life is too exhausting.

Claude Sonnet 4’s code ability I can’t praise too much. Previously encountered a code bug—Vibe Coding with Sonnet 4 made it worse. Pure waste of my time. Not understanding code logic, can’t hit targets precisely. Finally switched to Gemini CLI—Gemini 2.5 Pro passed first try. If someday Gemini CLI can share quota with Gemini web membership, definitely will see growth. Currently still underestimated.

Currently only Anthropic’s Claude model has such harsh usage limits. Pro users with longer Claude Opus conversations hit limits in no time.

GPT-5 releasing this week (US Thursday, Beijing Friday), but personally believe it still can’t shake Claude model’s strength in coding and Agents. What’s GPT series strong at? Most versatile, search, text-to-image, ChatGPT Agent.

Wonder if OpenAI’s benchmark this time dares to include Gemini 2.5 Pro, Grok 4, Claude Opus 4.1 comparisons. Even if included, I won’t believe claims of leading Claude in coding and Agents.

Recently I started habitually using English with various overseas models. Initially thought English prompts would waste time, but after practicing found it doesn’t waste much time. English expression using common words is enough. English phrases I can’t recall—directly use Google Translate to supplement. Even if my English prompts have spelling errors, as long as not outrageous, AI basically understands.

What’s most annoying about Claude models: You're absolutely right!

Writing up to here, time has passed 8 PM. I should wash up and prepare to rest. Finally attaching my prediction for future Claude releases:

Official blog⁴ has this sentence:

We plan to release substantially larger improvements to our models
in the coming weeks.

in the coming weeks Chinese translation: next few weeks.

Claude Opus 4.1’s most likely release time range is August 20 - September 3, 2025.

Claude Opus 4.1 predicts most likely release is Claude Opus 5, followed by new pricing tier, or longer context products.

Personally think its guesses have merit. After GPT-5 release, using massively improved models to crush OpenAI’s proud products benefits further expanding Claude model market.

New pricing tier also possible. Late August, Claude Max plan will add weekly quota limits to prevent fanatics using Claude Code 24/7 automation. For unlimited Claude Opus model usage, introduce new plan tier—pay more monthly, like $1000 or $2000.

Longer context also possible. 200K context, enterprise 500K context—still hasn’t reached Gemini’s 1M context window. Extending to larger context like 1M or 2M helps compete with GPT-5, Gemini models. But actually long context has drawbacks—even with strong decay resistance, hard to fully grasp massive text in context window.

Manus Experience

Thu, 17 Jul 2025 14:33:10 +0800

Update (2025.7.19)

With ChatGPT Agent’s release, Manus has become more active, like sharing dry goods articles on building Agents: Context Engineering for AI Agents: Lessons from Building Manus. Pressure from new competitors creating motivation is good.

Manus leaving China is a helpless move. Product has drawbacks but also advantages. Agent products definitely have many flaws—after all, Agent’s biggest problem is instability.

Remember early this year, using Claude 3.5 Sonnet as Agent framework base model, tools could be called stably within the same workflow. When Claude 3.7 Sonnet came out in February, after base model upgrade, the model started overthinking, sometimes not calling tools. Recently using Claude Desktop with MCP protocol calling external tools—even the strongest Claude Opus 4 doesn’t perfectly execute the same flow every time.

Give Agent products some time.

0 Introduction

A while ago I was learning about Agents. At that time, non-membership Manus experience felt very dumb. So on July 4, 2025, I used WildCard to subscribe to Manus Basic membership. Unexpectedly a week later WildCard shut down. After WildCard website came back online, I quickly spent the remaining balance on my virtual card. Also a week after subscribing, Manus left mainland China—this news received much criticism.

This post shares Manus Basic membership experience.

1 First Things First

First, Manus as a product—non-paying user experience is very poor.

Non-paying Manus accounts—the Agent base model probably isn’t Claude. During deep experience, free Manus Agent has extremely high error rate—among the worse free Agent products. Below shows asking free Manus to verify if Q&A pairs are accurate—only did one search. Needless to say, answers were inadequate.

After paying for Basic membership, Agent preference automatically switches to Quality.

Now Manus Agent’s effort level has qualitatively improved.

When using, recommend adding a Knowledge entry to Manus Knowledge as shown below—otherwise Chinese questions searching CSDN and such sites would be awkward.

After adding this Knowledge, generally Manus does Knowledge recall before searching internet, ensuring English search first. Only when English internet truly lacks resources does it search in Chinese.

2 Pros

2.1 Beautiful PPT creation

Thanks to OpenAI GPT Image 1 model integration, generated PPT is richly illustrated [though PPT also has inaccurate statements]. Tiangong/Skywork-generated PPT is also beautiful—images are cached from internet, not AI-generated [below shows Tiangong PPT agent’s PPT, but unfortunately has wrong information]. Z.ai, Genspark-generated PPTs are also nice but text-heavy without images—not my taste.

Heard OpenAI is also releasing Agent Mode soon—can directly edit PPT. If combined with OpenAI’s strongest text-to-image model, Manus probably becomes irrelevant.

2.2 Mini computer interaction is trendy but struggles with anti-crawling

Manus right-side mini computer interaction is trendy—I really like this experience.

But must point out current agent computer operation drawbacks: can’t pass human verification.

Above shows Minimax Agent blocked by Google human verification. Remember when Manus mini computer encountered Cloudflare Turnstile, I manually controlled the mini computer multiple times, clicking Cloudflare’s human verification button—kept spinning in infinite loop. Shows Cloudflare’s human verification is really impressive.

3 Cons

3.1 Poor public web data discernment

Since public internet materials vary in quality, Manus can’t properly distinguish correct from incorrect—accepting everything or fragmentarily understanding articles. Final result is flaws in replies.

Below shows paid Manus misunderstanding public internet material content, giving flawed reply.

At this point, adding user clarification can make Manus correct. Below shows Manus successfully correcting after my clarification guidance.

Same question—Minimax Agent, ChatGPT o3, Flowith trial membership all properly identified errors in original Q&A pairs. In this case, Manus Basic membership lost to these products. Below shows Minimax Agent identifying errors in original Q&A pairs in one go.

3.2 Non-transparent models

What base models for Adaptive, Agent, Chat modes—completely unmarked. Not much info online about Manus’s models either.

In Manus Discord group, late June, users guessed Manus Agent base model is Claude 3.7 Sonnet, Chat model is Gemini 2.5 Pro. Probably still the same mid-July—Agent base model not yet switched to Claude 4. Can’t rule out already switched to Claude 4 possibility. Either way, Manus needs to improve model transparency.

Gemini 2.5 Pro’s best experience is AI Studio + enabling Grounding with Google Search. Nobody would want Manus’s Chat.

3.3 Other cons

Scheduled tasks not as clear as Grok’s. Cloud browser—I currently have no use case. Official tweet example shown below. Text-to-image I prefer directly using ChatGPT. Text-to-video has Veo3 in Gemini App…

4 Summary

Manus feels like pure hype—hosting various events worldwide periodically, but very few features serve as moat. Events even in Nepal—quite surprising.

I’m pessimistic about Manus’s future. Given current trend of LLM vendors natively providing Agent LLMs, Manus will be in the same boat as Perplexity. Nearly $20/month for ChatGPT is better value.

Tools are Agent products’ moat. Like Grok can connect to X platform.

Meanwhile, Agent products are easily disturbed by variable-quality internet information. Chinese internet is essentially composed of various private domains (WeChat Official Accounts, Xiaohongshu, etc.). Public internet has less high-quality information. If Agent products’ models have weak discernment, getting disturbed by low-quality info leads to replies seriously citing wrong information.

A recent archived blog post, After Kimi K2 Release: No Longer Just ChatBot, had a statement that resonated with me: The vast majority of Agent products, without Claude, are nothing. The original page is offline. Reality is indeed so. Claude leads by far in Agents. Looking forward to Anthropic upgrading web Extended Thinking to Agent in the second half of the year after Claude Code programming Agent, while maintaining classic LLM.

Grok 4 Real Experience

Sat, 12 Jul 2025 08:28:46 +0800

0 Introduction

Elon Musk released Grok 4 at Beijing time noon on July 10. After my nap, right when the launch ended, I immediately used Grok 4 through an AI pooling platform.

Combining these days’ real experience and some valuable opinions online, sharing my real usage feelings.

1 Pros

1.1 Data source includes X platform

For Gemini, native Google Search enhancement elevates its capability. For Grok, X platform’s high-quality data makes it stand out among AI products.

X posts are unique to Grok. Other AIs connecting to internet mostly = connecting to web pages.

Overall, X platform has far more English high-quality data than Chinese high-quality data. X platform attracts many Chinese users mainly for NSFW content like daily competitions, plus lots of ads and random junk.

1.2 Agent LLM

Second LLM vendor natively providing Agent LLM [not counting Minimax, Tiangong and other agent products]. The Agent LLM I’m referring to is Chat and Agent combined, not separate. First was ChatGPT o3 model, third will be Gemini’s Agent Mode [reportedly coming in a few weeks, Ultra-exclusive]. Grok 4 is second.

This Agent LLM’s biggest use for me is fact-checking. Like when I collaborate with Claude on paper writing, after first draft of a paragraph and manual verification, I generally have ChatGPT o3 model verify the expression again.

1.3 Low censorship

Low censorship was already Grok 3’s biggest selling point.

Recently Grok got caught up in anti-Semitic, atomic bomb fireworks and other PR storms. Meanwhile, Western bloggers found Grok tends to reference Elon Musk’s views [Musk’s toy]. Hope Grok continues maintaining low censorship—sometimes politically incorrect statements are quite interesting.

Human world’s opinion texts are used to train Grok, meanwhile Grok’s reference materials also come from humans. Adding guardrails to LLMs is meaningless—censorship allowing only one voice actually breeds bias.

1.4 Grok Task

I was already looking forward to Grok 4 when Musk first announced July 4th release, but unfortunately it didn’t release as scheduled. Then I set a scheduled task in Grok to check daily if Grok 4 was released. The email notifications’ beautiful layout deeply attracted me—this experience is far superior to ChatGPT and Gemini.

2 Cons

2.1 Image recognition capability

Chinese image recognition is poor. English uncertain, but expected image recognition can’t match Gemini and other models.

2.2 Deep Research base

Initially thought Grok pooling site doesn’t offer Grok 4 Deep Research. After seeing Super Grok review content, realized Deep Research base model doesn’t support switching to Grok 4 yet.

2.3 Chinese experience lower than English experience

Yesterday saw an L Site post—Grok 4 isn’t bad actually, but I won’t use it. This comment caught my attention. Perhaps one reason for the Chinese vs English community reaction gap to Grok 4 is language. Though Grok 4 sometimes converts user Chinese questions to English before proceeding with tasks.

Whether to use Chinese or English for Grok 4 questions—depends entirely on context. If Chinese context works better, ask in Chinese. If English context works better, ask in English.

3 Summary

Grok 4 currently serves as a ChatGPT o3 model competitor on my local computer. Technical questions I generally ask Claude and Gemini. Fact-checking, news, etc. can consider Grok 4. Currently ChatGPT mainly uses o3 model for fact-checking.

But these are just generalities—comparing various top models is the norm. Like last night I asked Grok 4 a technical question—a US New York VPS I bought in April couldn’t connect to npm service. Grok 4 suggested changing VPS DNS settings. After following its advice, VPS could connect to npm normally.

Currently, no way I’ll pay full price for SuperGrok. $30/month not worth it. Pooling or freeloading SuperGrok around June 20’s last batch of edu discount accounts is optimal. The pooling site I use—Grok pools are usually idle, while Claude, ChatGPT, etc. get busy. Seems everyone’s not interested in Grok 4.

Before Grok 4, only one roommate commonly used Grok 3 model. This roommate had previously subscribed to ChatGPT and Claude memberships but has now switched entirely to freeloading. When chatting, one of his statements left a deep impression: “AI services are all pretty much the same.” This is indeed true—giving weak context to top models vs giving rich context to second-tier models—maybe second-tier solves your need while top-tier can’t. Besides, Grok 3 was also among top model ranks at that time.

Supplement

Updates to this Grok 4 article—see Flarum post—Grok 4 Experience Notes.

References

Claude 4 Review: Opus, Sonnet, and Claude Code

Fri, 23 May 2025 07:56:34 +0800

Update (2025.7.23)

Claude Code is no longer a toy. With Claude 4 series models online, Max membership paired with Opus 4 model is just too good. Those who know, know—the strongest AI programming tool!!! In just 1-2 months, successfully turned Cursor from sweetheart to has-been. Only Anthropic entering the arena could do this.

Update (2025.5.23)

Future updates for this Claude 4 article moved to Flarum post—Claude 4 Experience Blog Update Summary

via: https://x.com/testingcatalog/status/1925606824662679917

If you follow AI news, every day feels like time is compressed. Monotonous repetitive life passes exceptionally fast when following AI’s pace.

Claude 4 released early this morning. Anthropic chose not to release models in toothpaste-squeezing fashion with decimal version increments anymore.

This change largely stems from Claude’s market being heavily eroded by ChatGPT and Gemini recently. If OpenAI’s GPT4.1 and Google’s Gemini 2.5 series coding abilities still had significant gaps with Claude 3.7 Sonnet, Anthropic would likely release Claude 3.8 Sonnet and continue hiding the Opus model to improve Sonnet.

Note: Actually coding benchmarks only provide a general direction. Before Claude 4’s release, Claude 3.7 could still compete evenly with Gemini 2.5 Pro—not every coding scenario would be won by Gemini 2.5 Pro. Anthropic develops models for real needs, destined to have significant contrast between benchmark and user experience.

Claude series models’ biggest impression on me is concise, non-redundant replies, sometimes with soul. Like recently I was reviewing for the Software Designer intermediate exam, reviewing my comprehensive knowledge mistakes. For options I didn’t understand clearly, I had ChatGPT 4o/o3, Gemini 2.5 Pro, Claude 3.7 Sonnet answer. Sometimes Claude 3.7 Sonnet’s answers were concise with details, sometimes Claude 3.7 Sonnet performed poorly among these models—knowledge breadth not matching the other two.

Last time I used Claude 3 Opus was second half of last year. Remember being assigned to review seniors’ thesis proposals. I directly sent all text parts from proposals to Opus model for improvement suggestions. Never used it again after, because Claude 3 Opus’s writing ability somewhat couldn’t keep up with Claude 3.5 Sonnet series.

If Anthropic had released Claude Opus 4 in February this year, 2025 graduates’ theses would have had one more excellent option. Opus model is customized for writing. Though I haven’t tested Claude Opus 4’s writing ability, predicted text human-feel is very high.

Claude 4

Latest model cutoff date

Compared to Gemini 2.5 series models’ knowledge cutoff of January 2025, Claude Opus 4 and Claude Sonnet 4 knowledge cutoff reached March 2025. Though current LLMs mostly have internet access, newer knowledge cutoff is always better.

Extended thinking with tool use (beta)

With thinking and search buttons enabled, Claude can use search tools. After getting search tool response, continues thinking, iterating, then gives reply. The example below demonstrates this feature.

Previously with both thinking and search buttons on, when Claude felt it needed internet search, it would use search tools, then directly give reply after search—wouldn’t think again based on tool call results.

Anthropic Developer Relations Lead Alex Albert’s tweet demonstrating this feature: https://x.com/alexalbert__/status/1925591751118684258

New model capabilities, Claude Code GA

More precise instruction following and other new features are good—benefits Agents. Claude Code section will be expanded later with my new experience impressions.

New API features

This part will also be expanded later.

Pricing, access tiers

Claude 4 series models pricing same as Claude 3 series—at this price, no matter how strong the model, hard to be widely adopted.

Claude Opus 4 in GitHub Copilot only for Pro+ users. Claude Opus 4 in Cursor requires enabling Max mode. Cost-effectiveness king Gemini 2.5 is a hurdle Claude can’t easily overcome.

Sonnet 4 open to free users, Opus 4 exclusively for paid users. Friends with means wanting to experience Opus—recommend getting Pro membership. API not worth it. Will also introduce low-cost Claude membership paths I know.

Benchmarks

Benchmarks look great—wouldn’t release if they didn’t look great. Now every LLM release self-claims current SOTA (State Of The Art).

Personally agree with Anthropic CEO’s statement that benchmarks are meaningless. Benchmarks definitely have distortion but roughly compare model capability strengths.

This image shows Claude 4 far ahead on SWE benchmark.

This image shows Claude 4 becoming current LLM SOTA.

On livebench.ai, Claude Opus 4 currently holds first place among classic LLMs. Reasoning models suit benchmark gaming, classic LLMs suit users’ daily questions.

For classic LLMs, Google has already combined reasoning models with classic LLMs. OpenAI’s strongest classic LLM is actually the official site’s ChatGPT 4o—with various rich tools assisting, user experience is also first-class.

Currently my first choice for classic LLM: Claude Opus 4 on Claude official site and ChatGPT 4o on ChatGPT official site.

Claude Code

Selected these two new commands to experience:

1
2

/install-github-app
/vibe

See ChatGPT o3’s introduction to /install-github-app command.

Possibly useful commands:

# Update package manager and install GitHub CLI tool
apt update && apt install gh -y

# Authenticate login using GitHub CLI
gh auth login

# Follow prompts, create a `personal access token (classic)` in GitHub,
# check `repo`, `workflow`, `admin:org`, `admin:public_key` 4 options.

Professional programmers can try using Claude Code GitHub Actions for various tasks. I won’t bother.

via:

anthropics/claude-code-action repository

Claude Code GitHub Actions quick start

/vibe command contains a vibe coding Easter egg.

Seeing Claude Opus 4’s explanation include Dao De Jing, can’t help but marvel at Chinese culture’s depth, though Anthropic CEO is extremely anti-China.

The Way Of Code website: https://www.thewayofcode.com/

Used Claude Code to improve the Hungry Bear game’s visual effects and sound effects I made last time. via: https://bear.gujiakai.top/

Related operation screenshots:

My mind was blank, didn’t review the code, just kept pressing Enter Yes to confirm.

Learn programming well—the stronger you are, the stronger you + AI become. Otherwise using Claude Code you’ll have little inspiration.

Recommend experiencing Claude Code on US VPS. Today’s release also included IDE tool (VS Code, etc.) integration—won’t experience that. Domestic machines not recommended for touching any Claude products—carelessness will get your account banned. Masters confident in traffic splitting and able to appeal after bans—go ahead and experience.

Claude API

Code execution tool
MCP connector
File API
Extended prompt caching

Official related tweet demo: https://x.com/AnthropicAI/status/1925633118104416587

A while ago I experienced similar code execution tools in Gemini API. Can only say Anthropic released this feature somewhat late. OpenAI’s code execution tool API was supported 1 year ago. File API is similar situation.

via: https://www.anthropic.com/news/agent-capabilities-api

Other

Claude Invite campaign

Claude’s new referral campaign. via: https://claude.ai/invite

More referrals = higher chance of winning 4 months Claude Max plan.

Interestingly the Claude referral campaign restricts some US regions. See Claude Opus 4’s explanation.

Friends reading this who haven’t registered Claude accounts can consider using my referral link to give me a tiny chance at free 4 months Max plan. via: https://claude.ai/referral/_0IX9uZm2w

Actually just look at this kind of lottery—regular users refer themselves, do a few and done (I got one entry). No need to max out 100. There will definitely be cases where someone with 100 referrals doesn’t win while someone with 1 referral wins. Getting that many referrals and coming up empty-handed would be devastating.

via: https://support.anthropic.com/en/articles/11408405-claude-4-invite-contest

Cursor, Windsurf, GitHub Copilot and other third-party integration

Windsurf CEO crying—Claude 4 model not provided to Windsurf immediately. Windsurf’s user base will probably be slightly affected. Currently writing this blog post in Cursor editor—got a free year with US edu recently. Cursor, GitHub Copilot, etc. integrated Claude 4 immediately.

via: https://x.com/_mohansolo/status/1925605908287250939

Some good resource links, references

a. Claude 4 official blog: https://www.anthropic.com/news/claude-4

b. Simon Willison’s Live Blog on Claude launch: https://simonwillison.net/2025/May/22/code-with-claude-live-blog/

Attending the event in person gets three months of Max plan. Envious.

c. Definition of Agent: https://simonwillison.net/2025/May/22/tools-in-a-loop/

Agents are models using tools in a loop.

d. Claude model comparison: https://simonwillison.net/2025/May/22/updated-anthropic-models/

e. Tweets from Claude official X accounts:

Alex Albert’s Claude 4 announcement

Anthropic’s Claude 4 announcement

f. Tibor Blaho’s Anthropic launch summary tweet: https://x.com/btibor91/status/1925641897369797038

g. Vibe Check: Claude Opus 4 blog: https://every.to/chain-of-thought/vibe-check-claude-4-sonnet

h. Anthropic official livestream: https://www.youtube.com/watch?v=EvtPBaaykdo

Other livestreams: https://www.youtube.com/@anthropic-ai/streams

i. Claude 4 System Card: https://www-cdn.anthropic.com/6be99a52cb68eb70eb9572b4cafad13df32ed995.pdf

Recommendations

If you encountered Claude account suspension, recommend reading two previous blog posts. Most recommended is using US Windows VPS remote desktop to reduce suspension probability.

If you don’t want to deal with Claude environment hassles, personally recommend searching Claude on Taobao for corresponding plans. There’s a shop called claude克劳德小屋—experience is good, new customers can try 24 hours for 1 RMB.

This relay site completely mirrors Claude official site—probably borrowed from L Site admin’s Fuclaude project. Like if I want to experience Research feature only open to Max, Team, Enterprise—I use this site at very low cost. Of course this Research definitely can’t match ChatGPT or Gemini’s Deep Research.

Another option is buying cheap $1/month Claude accounts [lasts 3 months]. Late February this year Claude had a $1/month for 12 months edu discount for specific US edu—if you caught that, also very nice.

Best option is definitely getting an edu email partnered with Claude, like Northeastern University—free Claude Enterprise account.

Summary

For Claude web usage, generally don’t recommend enabling Extended thinking. Daily use classic LLM is enough—only consider enabling thinking when classic LLM replies are unsatisfactory.

Though Claude Sonnet 4’s SWE benchmark is slightly better than Claude Opus 4, and some benchmark code evaluations show Claude Sonnet 4 is better than Claude Opus 4, on Claude Web I’ll definitely prioritize Claude Opus 4 without thinking. For writing, code-related tasks in the future, first choice Claude Opus 4 is definitely excellent—only consider asking Claude Sonnet 4 if Opus 4’s reply is unsatisfactory.

Claude 4 is out—can GPT 5 be far behind? Looking forward to seeing GPT 5 model in mid-late 2025.

Google I/O 2025 Notes

Wed, 21 May 2025 08:01:38 +0800

Update (2025.5.21)

Future updates for this post moved to Flarum post—Google I/O 2025 Blog Update Summary.

Woke up this morning to see Google released a ton of new stuff. Can’t help but marvel at Google’s power—the future definitely belongs to Gemini (It’s Gemini Season¹). Though recently my ChatGPT usage for daily questions far exceeds other AIs.

Google I/O 25 Keynote YouTube video opening animation was all Veo-generated. via: https://youtu.be/o8NiE3XMPrM

Many AI enthusiasts’ X posts expressed that Google’s updates are overwhelming—hard to keep up. So much information—without organizing now, will miss major updates.

via: https://x.com/testingcatalog/status/1924899785355510239

This article aims to be a first-hand Google announcement relay while adding my own thoughts as much as possible.

First, some good Google I/O 2025 summary links:

NotebookLM’s Google I/O 2025 summary: https://notebooklm.google.com/notebook/953b658a-579b-4b3c-b280-43b3781babf3

Tibor Blaho’s Google I/O 2025 summary tweet: https://x.com/btibor91/status/1924938391478468754

Chubby’s Google I/O 2025 summary tweet: https://x.com/kimmonismus/status/1924895087332405554

X’s hot comments about 2025 Google I/O: https://x.com/i/events/1922336973353598976

Gemini App

This section mostly from the full official update blog post² and official Gemini App Updates page.

This section introduces Ultra-exclusive features or models not released immediately but coming to Ultra subscribers soon, so Ultra subscription currently has very low value.

Emphasis: English experience > Chinese experience

First must emphasize: Gemini App Chinese experience isn’t as good as ChatGPT or domestic Doubao.

English questions get well-reasoned replies with reference citations.

Chinese questions get replies without reference citations, sometimes feeling inadequate. Recently saw many L Site posts about Gemini dumbing down—this is actually a misunderstanding. Google with its deep pockets wants to steal all ChatGPT users, won’t do sneaky dumbing down. So-called “dumbing down” is actually due to insufficient Gemini App Chinese user support.

For better Gemini App experience, when Chinese replies aren’t satisfying, recommend rephrasing in English. For those not good at English, can pair with “Immersive Translate” browser extension—triple-space to convert native input to English; set shortcut to translate model replies back to native language.

New pricing plans

Gemini Advanced/Google One AI Premium renamed to Google AI Pro.

Besides some rate/context length differences, Pro users have over free users: Flow [an AI video creation tool, mentioned later], Gemini in Chrome [similar to Copilot in Edge, mentioned later].

Ultra users have over Pro users: Gemini 2.5 Pro Deep Think model, Veo3 model, Project Mariner [browser Agent], YouTube Premium individual plan, larger storage.

Ultra plan: $125/month for first three months, then $250/month. Initially tempting, but after calming down, no impulse purchase. After all, reasoning models thinking more—often just good benchmark scores. Daily use, classic LLMs are enough. Better reasoning model use cases: logic, math, code.

Heard about Project Mariner last year end. Hearing the name again today feels unfamiliar—browser Agent prototype still feels like a toy.

As for YouTube membership, few would get US region YouTube membership—usually low-price regions, joining Latin American family groups.

30TB storage is useless for regular people. All my files and photos on Google, accumulated 2-3 years, haven’t exceeded 200GB.

Ultra subscription suits wealthy folks or extreme Gemini AI enthusiasts/Google die-hard fans. For students like me, just watch—freeloading up to Pro plan is enough.

via:

Google AI Ultra announcement

Agent Mode

This feature looks nice, Ultra-only. See Google CEO Sundar Pichai’s tweet: https://x.com/sundarpichai/status/1924909900033122466

Gemini 2.5 Pro Deep Think, Gemini 2.5 Flash

Gemini 2.5 Pro Deep Think Ultra-only, benchmark data looks great. 2.5 Pro DeepThink API only open to a small group of trusted testers.

Gemini 2.5 Flash cost-effectiveness improved further.

Thought Summaries

Thought summaries aim to further improve model output interpretability.

Veo3, Imagen4

Veo3’s feature is text-to-video with sound—interesting, should be world’s first text-to-video with sound model. Only US Ultra subscribers can experience.

Imagen4 open to all Gemini users. Below shows a raccoon holding a sign generated with Imagen4. For text-to-image, GPT-4o native text-to-image and recent Doubao’s Seedream 3.0 seem impressive.

Grok leads by far in low censorship—this is unique. Few days ago had Doubao generate borderline images—Doubao directly refused for sensitive Chinese prompts. Had Grok translate prompt to Russian [ChatGPT refused translation request for borderline prompts], broke Doubao’s guardrails. Sometimes can’t help but feel Grok shouldn’t be ignored—low censorship is its biggest selling point. Probably Grok 3.5 coming soon—hope it surprises everyone!

Gemini App media-generation announcement on X

Gemini App media-generation follow-up on X

Deep Research creating apps/Canvas updates

After Gemini Deep Research, can create apps. Besides preset operations: Web page, Infographic, Quiz, Audio Overview (podcast), can also create custom apps. Don’t recommend custom app creation—custom apps have bugs.

Facing walls of text makes people impatient. This feature directly solves Deep Research products’ visualization insufficiency.

via: https://x.com/GeminiApp/status/1924892563695456675

Image and file-based Deep Research

Image-based Deep Research use case I thought of: ~~JAV code Deep Research~~ [Actually too much—Gemini App high censorship, any slightly explicit image gets removed. But if asking to find actors in image (premise: image NSFW content is low), can Deep Research]. Removed related explicit images; guessing locations from photos.

Below shows Gemini guessing location from the same image I gave ChatGPT o3—results lacking. ChatGPT o3 is better at guessing locations from images. Actually had Doubao guess from this image before—Doubao’s deep thinking felt jumpy but got the location right first try. For guessing domestic photo locations, domestic AIs are better—giants have tons of Chinese data.

ByteDance’s Doubao is already Top 1 domestic AI in my mind. Doubao doesn’t offer one-click conversation deletion option—destined that all user data will build Doubao’s throne. Almost all AI providers are the same—surface level not violating privacy, not using user data for training, secretly decoupling data from accounts and quietly improving products. Such operations are too common.

Below shows using Gemini Deep Research to study DeepSeek’s latest paper—file-based Deep Research should have many practical use cases.

via: https://x.com/GeminiApp/status/1924892309583458706

Other

Gemini Live free on Android and iOS.

Many are already Google AI Pro users. Friends who haven’t claimed the deal—can consider getting a US edu email [no longer limited to US—Brazil, Indonesia, Japan, UK edu emails qualify] and claim this freebie before June 30 this year (https://gemini.google/students/).

via:

Gemini App feature announcement on X

Google feature announcement on X

Gemini API

This section mostly from official blog post³.

gemini-2.5-flash-preview-05-20

Improved Gemini 2.5 Flash model with better performance.

Gemini 2.5 Flash and Gemini 2.5 Pro will be GA (Generally Available) in early June 2025

Google models’ inherent release rhythm: Experimental—Preview—GA.

Logan Kilpatrick’s Gemini API announcement on X

Gemma 3n E4B

Mobile-centric open-source model—good for open source. Regular users have better closed-source options.

via:

Gemma 3n developer announcement

Gemma 3n preview models on Hugging Face

Gemma 3n documentation

Gemma 3n discussion on Hacker News

Native audio output and Live API improvements

Stream section added gemini-2.5-flash-preview-native-audio-dialog and gemini-2.5-flash-exp-native-audio-thinking-dialog models. Both are Gemini 2.5 Flash Native Audio. Early features include Proactive audio, etc.

Conversational assistant apps can consider integrating—Chinese works well too.

Generate Media section—>Gemini Speech Generation, added text-to-speech models—gemini-2.5-flash-preview-tts and gemini-2.5-pro-preview-tts, can generate voice from scripts.

AI Mode

English only. Kicking Off, Looking At flow to answer user questions—interesting. Previous AI Mode probably didn’t have these two prompts.

AI Mode for political figure searches only provides links, no generation.

New AI Mode features shown at I/O including Deep Search will roll out to AI Mode Labs users over coming weeks and months.

Google Search AI Mode update

Gemini Diffusion

Google’s text diffusion model. Users with access say: incredibly fast. First commercially deployed diffusion model LLM is Mercury.

via:

Gemini Diffusion announcement

Gemini Diffusion demo on X

Gemini Diffusion discussion on Hacker News

Gemini Diffusion model page

Flow

An AI video creation tool. See ChatGPT o3’s introduction.

Played around and generated a US kitty captain in space.

via:

Google Flow

SynthID Detector

Project for quickly and efficiently identifying if AI-generated content contains SynthID watermark. See ChatGPT o3’s introduction.

Content generated in Gemini App started having watermarks last year (via: https://deepmind.google/discover/blog/watermarking-ai-generated-text-and-video-with-synthid/). So friends using Gemini for writing assistance—remember to have other LLMs rewrite. Though domestic AIGC detection hasn’t added SynthID yet, can’t rule out future addition. If added, can self-check with SynthID Detector first.

via:

Google SynthID Detector announcement

Stitch

AI prototyping tool for design-to-development one-stop flow. I’m not a designer—designer friends can pay more attention.

Has Standard Mode [Gemini 2.5 Flash powered] and Experimental Mode [Gemini 2.5 Pro powered].

Stitch-generated page praising Trump.

Remember to disable Stitch conversation data training in settings—though Google probably won’t strictly comply.

Google Chrome Gemini

Similar to Copilot in Edge. Summarizing webpages is a nice option, though it’s a bit sticky.

Google Chrome Gemini announcement on X

Project Astra

Joined the Waitlist last year end—still haven’t gotten to experience it. Disappointing. Project Astra demo videos on Google’s YouTube channel have high views—shows Project Astra is highly anticipated.

After watching Project Astra’s latest demo videos—Helping handsome guy assemble bicycle, Helping girl with chemistry learning—I also want such a universal AI assistant.

via: https://deepmind.google/models/project-astra/

Try it on

Virtual try-on feature from Google Shopping. Upload full-body photo for virtual try-on.

Grabbed a random beauty full-body photo from Xiaohongshu for experiment—effect is great.

Original:

Virtual try-on:

Google Shopping virtual try-on guide

Android XR

Not familiar with this area. See ChatGPT o3’s introduction.

Android XR announcement

Android XR with Gemini announcement

Google Meet Real-time Translation

Initially supports English and Spanish. See related demo video.

Web comment: Google just ended my translation career. This feature is promising.

Other

Still some not covered, like Lyria 2 [Google’s music generation model], Google Beam [video conferencing stuff].

As for Jules [Google’s AI code Agent], I tried it yesterday—felt average. Still need to learn programming properly. AI-assisted learning speeds up progress. Just Vibe Coding all day—end up being nothing without AI.

Summary

Day 1 Google I/O 2025 announcements roughly these. Day 2 usually no major announcements. This week is destined to be extraordinary—whether o3-Pro, Grok 3.5, Claude 4 coming, stay tuned. Anthropic has an event at midnight Beijing time May 23, 2025.

Google launching Ultra plan shows following OpenAI’s path. High pricing means destroying AI democratization. But Google already laid groundwork letting users freebie 15 months Gemini membership—won’t criticize high pricing too much. The model baseline leading into these announcements is covered in my earlier Gemini 2.5 Pro experience.

My most-used AI app has switched to ChatGPT. Though I haven’t abandoned Gemini, Claude, etc., overall ChatGPT feels best in all aspects. From earlier text, you saw for new knowledge points, I basically use ChatGPT o3 model for research. This Agent LLM is just too convenient—excellent UX. Unless replies are unsatisfying, generally too lazy to open search engines.

Can say ChatGPT-style Agent LLMs deal a big blow to Perplexity-type AI search wrappers. I believe future Google’s similar o3 Agent LLM might directly sentence Perplexity-type products to death. What’s Perplexity’s moat? Nothing—models are outsourced, web data is outsourced. Eventually will be consumed by these giants.

Some interesting content seen today:

ChatGPT o3, o4 mini Experience

Thu, 17 Apr 2025 09:06:26 +0800

Update (2025.4.29)

Personally I feel ChatGPT 4o model has improved a lot compared to last year. Recently saw an L Site post—Is 4o’s sycophantic style GPT dumbing down—can’t help but think for newbie users, 4o’s sycophantic style is indeed friendly.

Currently for some daily questions (not involving programming, writing), I’m leaning toward ChatGPT 4o. Comparing today’s Qwen3 release—Qwen3 benefits open-source which is commendable, but for daily topics, I personally think it’s slightly inferior to closed-source models. [Though one example below isn’t enough to show the gap]

Nobody rejects a sycophant [as long as they catch your eye]. I definitely won’t reject Doubao’s sweet girl voice or ChatGPT 4o’s sycophantic style. 😁

“OpenAI though Closed is always at the top of the entire industry”—this statement makes so much sense! Non-dumbed-down OpenAI has unbeatable experience in all aspects. via: https://linux.do/t/topic/602275/

Update (2025.4.26)

Today ChatGPT 4o on official site updated again. via: https://x.com/sama/status/1915902652703248679

After using official site 4o a few times, for technical questions, ChatGPT 4o now prioritizes English internet search. This is good. Previously Chinese questions searched Chinese internet.

Recently I increasingly feel products like Perplexity will die in the future. Since o3, o4-mini series models came out, my Perplexity usage dropped sharply.

Update (2025.4.24)

ChatGPT Plus users’ o3, o4-mini-high quota doubled. o3: 100/week; o4-mini-high: 100/day.

via: https://help.openai.com/en/articles/9824962-openai-o3-and-o4-mini-usage-limits-on-chatgpt-and-the-api

Update (2025.4.20)

Can’t completely embrace Claude either. Currently ChatGPT’s latest o3, o4-mini series full-auto agent LLM calling various tools for debugging is really comfortable. Code comments might not match original o3-mini-high, but everything else is far ahead. Previously for internet debugging I might use Perplexity etc. for assistance. With latest o3, o4-mini-high—full-auto debugging, Chinese programming questions, English internet search, until task complete.

For example, this morning while learning I encountered a bug. Asked various LLMs—only ChatGPT’s full-auto agent successfully solved it. Other LLMs I didn’t even want to follow up—initial answers were problematic. Plus solving this bug needed searching latest knowledge—way more effort than ChatGPT’s full-auto agent.

I can only say current LLMs are truly dazzling. Sometimes don’t know which model to use. Because I personally have strong Claude inertia, yesterday I wrote Claude praise, but recent Gemini 2.5 Pro, ChatGPT o3, o4-mini series updates are also really top—all SOTA. Having choice paralysis.

Update (2025.4.19)

Recently o3 guessing image locations went viral. But besides image guessing, the rest feels below expectations. Like code comments—I somewhat miss o3-mini-high. Current tool-using o3 or o4-mini-high has insufficient thinking time—code comment quality worse than original o3-mini-high.

Whenever I learn new knowledge, I still first consider Claude. Gemini 2.5 Pro can’t achieve Claude’s rich yet not overly verbose communication experience. Claude sometimes has excellent generalization (so-called soul)—incisive replies to questions feel surprising yet unexpected. Though I compare all current LLMs, overall after getting used to Claude’s reply style, so far no LLM catches my eye. No matter how Gemini 2.5 Pro, o3, o4-mini-high dominate benchmarks, my heart always belongs to Claude.

Update (2025.4.18)

Context decay resistance

o3’s powerful context decay resistance surpasses Gemini 2.5 Pro. Still the big brother OpenAI—far ahead. Pro users with unlimited o3 probably won’t even glance at o4-mini-high. In a few weeks o3-pro comes out.

via: Fiction.liveBench April 17 2025

Daily usage choice

For not-too-complex questions, prioritize o4-mini-high—after all, Plus users have limited weekly o3 quota. Personally, agent mode o-series has excellent user experience.

Update (2025.4.17)

Adding some good review content I’ve seen.

Original Long Post: Everything about GPT-O3, O3-Pro, O4-mini and 4.1: Livebench, Aider Coding, SimpleBench All Top, Free Trial Channels [Long-term Update]

Update Summary

Usage limits

ChatGPT Plus users: o3 limit 50/week; o4-mini limit 150/day; o4-mini-high 50/day; 32K context window.

via:

OpenAI o3 and o4-mini usage limits

ChatGPT plans and pricing

Don’t recommend free users use ChatGPT. Without paying, experience is definitely terrible—only 8K context window, and only lower-tier models available.

In OpenAI’s rules, Pro users are gods, Plus users are commoners, free users are beggars.

Also don’t recommend friends with obvious proxy characteristics to use ChatGPT—dumbing down is real. Suggest remote Windows desktop/self-hosted KasmWorkspaces methods [prerequisite: remote VPS IP should be clean, otherwise still dumbed down] to access ChatGPT.

Reasoning model becomes agent, combining every ChatGPT tool (web search, Python interpreter, image analysis, file interpretation, image generation), can do visual reasoning [multimodal reasoning]

Image below shows part of image recognition task—feel ChatGPT o3 model’s terrifying iteration capability.

This image recognition task flow—see this task’s webpage screenshot:

1m21s reasoning time

Find drone in image.

44s reasoning time

Initial guess of possible photo locations [guess list already contained correct answer, unfortunately bet on one—most likely guess was wrong.]

2min59s, 4min41s, 11min14s, 12min41s, 13min56s reasoning time

In these parts, o3 uses internet tools to guess possible locations, but possibly hit reasoning time or context limit, causing truncation—only outputting to=.

Couldn’t watch o3 deviate from correct answer, going further in wrong direction. I revealed some hints—like initial guess list has correct answer.

6min51s, 11min45s, 13min51s reasoning time

I saw o3 flip-flopping between correct and wrong answers, falling into same predicament—only outputting to=. Continued revealing hints—don’t fixate on one area’s universities, don’t limit to library-type buildings.

7min14s, 9min31s, 11min58s reasoning time

o3 again interrupted. I continued prompting—combine above analysis, give most likely location.

10s reasoning time

o3 successfully guessed the location, but small location was wrong.

11min56s reasoning time

o3 with search successfully guessed small location, but response contained wrong info.

Finally I asked o3 to convert original image to Ghibli style

Looking back—this is truly a cheesy strategy, but also how agents should be—using external tools to iterate until task complete.

First time experiencing LLM reasoning over 10 minutes. ChatGPT really tries hard.

Daily usage: choose o3 or o4-mini-high?

From OpenAI’s benchmarks, except these three (first two test math competitions, third is algorithm programming competition) where o4-mini-high leads o3, the rest o3 wins.

OpenAI employee recommends o4-mini-high over o3 for visual tasks. via: https://simonwillison.net/2025/Apr/16/james-betker/

Though benchmarks have biases, they roughly show LLM general capabilities. OpenAI’s new models dominate livebench.ai—reasoning models are indeed benchmark kings.

Plus users have 50/week o3 quota—use it. After exhausting o3, use o4-mini-high.

New models’ search: Chinese questions no longer limited to Chinese internet

After Chinese questions, OpenAI’s new o3, o4-mini series directly search internet with English and Chinese versions of the question. GPT-4o still follows Chinese questions, Chinese internet search.

Reinforcement learning training models to use tools is truly impressive—not just teaching how to use tools, but reasoning when to use them.

Codex

Similar to Claude Code. I tried applying for open-source funding—if they give me some API quota, I’ll try. Not considering for now. Foreigners think OpenAI finally gets it—starting to learn from Anthropic developing models for real needs.

Other discoveries

OpenAI’s new models are token efficient (use as few tokens as possible for same or better information expression and reasoning).

I think this is the future trend for reasoning models. Current OpenAI new models already feel like reasoning models + classic LLM combined.

Gemini 2.5 Pro remains cost-effectiveness king.

via: https://x.com/MahawarYas27492/status/1912577363554214214

Comparing aider leaderboard top spending shows Gemini 2.5 Pro is truly cost-effective. DeepSeek V3 March update is also cost-effective but capability-wise inferior to Gemini 2.5 Pro.

via: https://x.com/bongrandp/status/1912568582426198301

via: https://x.com/wintermoat/status/1912560505161400781

Summary

OpenAI new models’ main highlights are tool calling and multimodal reasoning.

This time OpenAI’s blog benchmarks only listed their own models. Is this arrogance—OpenAI thinks their models are strongest? Or not daring to compare with other advanced models, fearing their massive users learn about other advanced LLMs? Only OpenAI knows.

But this release is much better than before. GPT-4.5, GPT-4.1 releases in today’s rapid iteration barely make waves. Only releases like GPT-4o native text-to-image, o3, o4-mini series are the right path.

Can say OpenAI Is Back! Though I hope to see open-source LLMs closer to closed-source, currently closed-source LLMs again widen the gap.

Looking forward to Qwen3, DeepSeek R2 performing better soon.

One more thing—OpenAI still releases reasoning models. Friends who like non-reasoning models—still don’t underestimate Claude 3.7 Sonnet Without Thinking!!!!!

Other

Attaching some other bloggers’ reviews

OpenAI Launches Full o3 and o4 mini Late Night - Still Leading.

References

Self-Hosted Kasm Workspaces

Mon, 31 Mar 2025 08:40:02 +0800

Update (2025.4.15)

About seamless clipboard

Seamless clipboard supports copying images directly from local clipboard to Chrome browser in Kasm Workspaces. Attaching images doesn’t need file upload as described below.

Supplement: Sometimes this method works, sometimes fails—feels unstable. This seamless clipboard has bugs.

About datacenter IPs

OpenAI indeed dumbs down models based on datacenter IPs. Example: I logged into ChatGPT on a garbage VPS from Colocrossing’s Windows VPS, asked o3-mini-high to think and write code comments—thought for 7s. Used common dumbing-down detection prompt: summarize your tool in a markdown table with availability. Found only 4 tools (missing US election tool). Non-dumbed-down ChatGPT has at least as many tools as below. Immediately decided not to renew Colocrossing this year.

If your VPS IP isn’t clean, don’t set up Kasm Workspaces to play with AI.

On a lesser-known US datacenter VPS [US East machine], logged into ChatGPT, asked o3-mini-high to think and write code comments—thought for over 2 minutes.

Indeed for OpenAI AI services, not just US residential IPs get full power—obscure clean datacenter IPs can also shine.

Update (2025.4.3)

Actually this solution’s experience isn’t as good as remote Windows desktop. Even with datacenter IP, remote Windows desktop’s proxy characteristics basically only have IP type issues—other characteristics are eliminated. Plus if it’s California machine, latency is low—good experience. Copying images, uploading files etc. much easier than Kasm Workspaces.

Kasm Workspaces suits friends who don’t want VPS as Windows but want good disguise for AI. Using overseas AI on East Asia timezone computers—might get telemetry detected someday. Traffic splitting isn’t foolproof. Fingerprint browsers also feel lacking.

Background

First time using Kasm Workspaces was 2023. Set up non-Docker version on a HostHatch Singapore machine but didn’t dig deep—just set up, tried various Workspaces like Chrome, Ubuntu desktop.

Let Claude 3.7 Sonnet briefly introduce Kasm Workspaces.

Desktop-as-a-service is actually very practical use case.

Then let Gemini 2.5 Pro explain the Workspaces concept.

Prerequisites

Preferably a VPS with IPv4 address and decent specs (4GB+ RAM)

IPv6-only VPS—I found during setup that after completing Kasm Workspaces installation wizard, couldn’t login to Kasm Workspaces page despite correct credentials. Didn’t investigate this bug—might only trigger in my test, not necessarily on IPv6-only machines.

Official docs list minimum requirements: 2 cores, 4GB, 50GB¹.

Preferably a clean Linux system

Some VPS providers’ Linux templates aren’t great—Docker-based KasmWorkspaces encounters various strange issues. Initially on my high-spec machine, self-hosting KasmWorkspaces had almost no issues. But while writing this article, testing machine had various bugs—process was frustrating. Recommend friends wanting to self-host choose a dd’d clean Linux system.

Setup Process

Setup follows docker-kasm project².

# Create kasm directory and enter
mkdir kasm && cd kasm
# Use vim to open or create compose.yml
vim compose.yml

compose.yml [note host ports 8443, 3000 are free]:

---
services:
  kasm:
    image: lscr.io/linuxserver/kasm:latest
    container_name: kasm
    privileged: true
    environment:
      - KASM_PORT=8443
    volumes:
      - ./data:/opt
      - ./profiles:/profiles
    ports:
      - 8443:8443
      - 3000:3000
    restart: unless-stopped

1
2

# Start services defined in compose.yml in background (detached mode)
docker compose up -d

Visit https://your_ip:3000 to enter Kasm Workspaces installation wizard.

Enter admin password, continue.

Choose Chrome, Edge, or Brave browser [pick one], click install.

After download completes.

Visit https://your_ip:8443/ to reach Kasm Workspaces login page.

Enter username admin@kasm.local and password from installation wizard to login.

User Settings

First thing after entering—don’t immediately Launch app Session. Do user settings first.

Can run this command on VPS to get timezone.

1
2

# Get VPS IP info
curl ipinfo.io/json

For example I got "timezone": "America/New_York".

Then in Kasm Workspaces, click admin avatar at top right for Edit Profile.

Set Kasm UI Language to English;

Set Kasm Session Language to English: United States of America;

Set Kasm Session Timezone to VPS’s timezone.

Other settings as needed, like two-factor auth.

Persistent Profiles

Reason for persistent profiles—Kasm Workspaces by default doesn’t save user Profiles config³. For example, if I login to ChatGPT in this Session, next Session requires re-login. With persistent profiles, only need to login ChatGPT first Session—next Session ChatGPT is already logged in.

Click ADMIN at top for related settings.

Click Workspaces—>Workspaces on left. My demo initially installed Brave browser. Click Brave browser’s Edit button.

In Persistent Profile Path enter /profiles/brave/{username}/. If default app is Chrome, can set /profiles/chrome/{username}. Then click Save to update Workspace settings.

Now when Launching Brave browser, you’ll see Persistent Profile option. Enable it.

Now launch Brave browser, login ChatGPT.

Then Delete Session from left control panel.

Next time launching Brave browser, ChatGPT is still logged in—this is the magic of persistent profiles.

Other

In ADMIN—>Access Management—>Users, can add and delete users.

I deleted user@kasm.local and added custom user.

Can open Kasm Workspaces page (https://your_ip:8443) in another local browser, login with new custom user credentials.

New user’s first thing after login—still do user settings [refer to earlier section for language, timezone settings].

Then we can login Claude account in this Session.

Since we enabled persistent user config, deleting this Session and reopening—Claude still logged in.

Cleanup

Set Zone Proxy Port to 0 [needed for reverse proxy]⁴:

ADMIN—>Infrastructure—>Zones—>default—Edit

Change Proxy Port from 8443 to 0 and Save.

Caddy reverse proxy config [make sure domain has proper A record]⁵:

kasm.example.com {
    reverse_proxy https://127.0.0.1:8443 {
      transport http {
        tls_insecure_skip_verify
      }
    }
}

1
2

# Reload caddy
systemctl reload caddy

Then access Kasm Workspaces via domain kasm.example.com.

Update Kasm Workspaces compose.yml to reduce exposed ports:

services:
  kasm:
    image: lscr.io/linuxserver/kasm:latest
    container_name: kasm
    privileged: true
    environment:
      - KASM_PORT=8443
    volumes:
      - ./data:/opt
      - ./profiles:/profiles
    ports:
      - 127.0.0.1:8443:8443
    restart: unless-stopped

1
2

# Stop and remove all containers, networks, volumes and images created by Docker Compose, start services in background
docker compose down && docker compose up -d

To install other Workspaces, select from ADMIN—>Workspaces—>Registry.

For AI queries, text content uses copy-paste. Kasm supports seamless clipboard for Chromium-based browsers⁶.

For copying images and other files—use left control panel’s Upload plus AI chat interface’s Upload feature.

After uploaded images accumulate, can clean up in profiles-related folders.

Use Cases

ChatGPT, Claude and other network-sensitive scenarios
AI account sharing
……

My current use case—one local browser opens Kasm Workspaces ChatGPT, another opens Kasm Workspaces Claude. Used for over a week—experience is decent.

Summary

Current AI services don’t necessarily need residential IP—not just residential IP avoids bans. I’ve given up on residential IP. Datacenter IP works fine as long as your datacenter isn’t Chinese-heavy [especially US West], IP isn’t too dirty. For example, ensure proxydetect.live detects only 2 proxy characteristics—greatly reduces dumbing-down and ban risks.

Of course using local proxy for overseas AI services with East Asia timezone characteristics might not be detected. But accessing OpenAI via Kasm Workspaces Chrome browser definitely eliminates this characteristic.

Both ChatGPT and Claude Kasm Workspaces running—nearly 4GB memory consumption.

OpenAI—that villain—in a February report already more or less revealed how they conduct so-called security activities⁷. Chinese prompts, Chinese working hours are significant characteristics. Not saying can’t use Chinese prompts—there are many Chinese Americans, can’t stare at Chinese forever.

OpenAI is truly a villain—curse them, still use them.

Eliminate obvious proxy characteristics via Kasm Workspaces, regularly clear chat history, destroy evidence—OpenAI definitely doesn’t prioritize these accounts.

Recommend friends with high-spec machines wanting stable ChatGPT, Claude access to set this up. If a graphical reverse-proxy manager fits the rest of your self-hosted stack, see the separate Zoraxy deployment.

Gemini 2.5 Pro Experience

Sun, 30 Mar 2025 14:29:10 +0800

Update (2025.5.7)

Future Gemini 2.5 Pro updates moved to my self-hosted Flarum forum post Gemini Updates Summary. For Gemini App, recommend asking in English—Chinese experience definitely isn’t as good as ChatGPT or Claude.

Yesterday news broke that Google One AI Premium student discount can be claimed without edu email verification. This morning checking news, saw Gemini upgraded again, from 0325 version to 0506 (Google I/O conference version). Meanwhile Cursor also launched a free one-year student plan. I just claimed this deal and am editing this blog post in Cursor editor, immersed in the joy of free AI perks, can’t help but marvel at AI’s rapid development.

Update (2025.4.19)

Google’s generous student giveaway official blog post: https://blog.google/products/gemini/google-one-ai-premium-students-free/

Important (2025.4.18)

Google with its deep pockets is amazing. US Edu email verification gets 15 months free. Direct freebie! via: https://gemini.google/students/

Enough said, Google is awesome, hope Gemini sweeps all LLMs sooner or later, dominating!

Update (2025.4.18)

This article will be used to record Gemini 2.5 series model update notes.

Gemini 2.5 Flash early preview released

Google’s first hybrid reasoning model, developers can adjust model’s thinking depth via thinking_budget parameter.

Available in AI Studio, Vertex AI, and Gemini App. In Gemini App, 2.5 Flash replaced the original 2.0 Flash Thinking.

For AI Studio pricing strategy, can refer to ChatGPT o4-mini-high’s analysis [not necessarily accurate, users with payment cards should watch for preview model charges]. I usually experience with non-card-linked AI Studio accounts, afraid of charges, my card-linked AI Studio account only used when calling API for batch data processing.

I definitely won’t prioritize 2.5 Flash since Gemini 2.5 Pro is currently the strongest Gemini model.

via:

Update (2025.4.17)

Gemini 2.0 Flash and 2.5 Pro in Gemini App support LaTeX rendering

via: https://x.com/joshwoodward/status/1912300138074444095

Gemini Live gradually rolling out to all Android users

via: https://x.com/GeminiApp/status/1912591827087315323

Update (2025.4.16)

Veo2 gradually rolling out to Advanced users in Gemini App, Veo2 fully launched in AI Studio.

via:

While organizing emails this morning, found Google gave me another three months of Gemini Advanced membership. This old account already had tried Gemini Advanced membership before. Can only say Google’s products are really affordable. Though privacy is poor—free users’ chat data will be used to improve Gemini—it’s truly good value. Compared to OpenAI and Anthropic, it’s way too cost-effective.

Claude launched Research feature today. After seeing the demo and that new features no longer open to Pro users, I shook my head. Following OpenAI’s old path is digging their own grave. Hope Gemini kills both these companies soon!

Update (2025.4.15)

Gemini 2.5 Pro also has pain points. When asking reasoning models to write code comments, they modify the original code.

Update (2025.4.12)

Gemini Advanced’s 2.5 Pro probably isn’t a chat-optimized version. Highly recommend friends subscribe to Google One AI Premium—after experiencing this long, Gemini Advanced experience is much better than before.

For low-cost continuous Gemini Advanced use, can buy monthly throwaway accounts on Taobao or Xianyu. I see some L Site friends do this. My current Google One AI Premium plan is $9.9/month after US edu email verification. See Google One Student Discount. Recently lots of US edu email student discount AI activities: $1/month Claude membership, free 2 months ChatGPT Plus, free 2 months Super Grok. All 4 major US frontier AIs can be had cheaply.

Can compare using 2.5 Pro models from Gemini Advanced, AI Studio, and Vertex AI Studio. Like this afternoon I had 2.5 Pro from all three places write code comments [nearly a thousand lines, Python file downloaded directly from Colab]. Gemini Advanced performed best, Vertex AI output a ton then errored out, AI Studio output a ton then had code block formatting issues. Note: best reply source varies each time. Currently for code comments I’m leaning toward Gemini 2.5 Pro—OpenAI’s o3-mini-high feels lacking.

The 1M context window is unbeatable. Claude’s 200K or 500K, ChatGPT Plus users’ 32K, Pro users’ 128K—all little brothers compared to Gemini. Plus Gemini’s context decay resistance is also top-tier. True LLM King!!!!!

Update (2025.4.10)

Expected future AI competitive landscape: Google’s leading advantage will grow larger.

When OpenAI launches expensive Pro plans, Anthropic follows OpenAI’s path with expensive Max plans, while Google continues offering free access to the most powerful LLM services. Paid Gemini Advanced membership besides nearly unlimited usage also includes Google One and other services—the value is obvious.

Update (2025.4.9)

Gemini App Deep Research powered by the most powerful Gemini 2.5 Pro model, available to Gemini Advanced users.

via: https://blog.google/products/gemini/deep-research-gemini-2-5-pro-experimental/

Update (2025.4.8)

Gemini Live further rolling out to Android users

Chinese voice options aren’t great, but Gemini 2.5 Pro model capability is outstanding.

via: https://blog.google/products/gemini/gemini-live-android-tips/

Gemini 2.5 Pro coding ability is indeed outstanding

After seeing many netizens’ praise for Gemini 2.5 Pro and combining with my own feelings, Gemini 2.5 Pro’s coding expertise indeed trends toward surpassing Claude 3.7 Sonnet. Overall, Gemini 2.5 Pro is far ahead—not only sweeping various benchmarks but user experience is also top-notch.

Dual-wielding Gemini 2.5 Pro and Claude 3.7 Sonnet is definitely the optimal solution currently [Since Gemini 2.5 Pro is currently a reasoning model, reasoning models excel in: logic, code, math, so in other areas still can’t underestimate Claude 3.7 Sonnet. Additionally, Anthropic develops models based on real needs, not benchmarks, which causes public underestimation of Claude!]. The AI closest to AGI form in the future very likely will be Gemini.

Update (2025.4.5)

OpenAI delays GPT-5 release

OpenAI delayed GPT-5 release, most likely because Gemini 2.5 Pro has reached GPT-5 level. Currently OpenAI’s integrated GPT-5 can’t crush all benchmarks, can’t beat Gemini 2.5 Pro.

Think about it—if you were Sam Altman, would you allow releasing a GPT-5 that isn’t far ahead in all aspects? I predict GPT-5 release timing depends on OpenAI actually developing a model that crushes all benchmarks, otherwise GPT-5 will forever be just a pie in the sky.

Continuing to release reasoning models is a sign of OpenAI barely surviving. Though the recent GPT-4o native text-to-image was indeed impressive, OpenAI’s iteration on basic non-reasoning models has been somewhat disappointing personally.

Developing models for benchmarks is a big taboo. I really appreciate Anthropic developing models for real needs—that’s the right approach to LLM development. Good user experience means no shortage of users. Even though Claude no longer tops various benchmarks, its good user experience always attracts me. Currently the better choice for Agent base models is also Claude.

Recently read many Gemini 2.5 Pro articles. Summary: Gemini 2.5 Pro is most cost-effective, arguably the current strongest model (LLM King), with reasonably controlled pricing.

Don’t think I’m always praising Claude—actually Claude isn’t omnipotent either. Current LLMs each have their strengths.

Gemini 2.5 Pro launches paid preview version

Experimental model with ID gemini-2.5-pro-exp-03-25 continues free. Preview model with ID gemini-2.5-pro-preview-03-25 starts paid preview, more competitive pricing compared to OpenAI and Anthropic. See Simon Willison’s blog post—Gemini 2.5 Pro Preview pricing.

Gemini 2.0 Pro no longer exists

via: https://x.com/OfficialLoganK/status/1908179750536827183

Update (2025.4.4)

My Gemini App also got Gemini Live Camera feature. Same old story—for Chinese voice see Doubao. Gemini Live Camera is better experienced in English—Chinese experience isn’t great. Currently Gemini App voice-to-Chinese seems unsupported, so don’t expect great experience with Live Camera. Fluent English expression is prerequisite for good Gemini Live Camera experience!

Update (2025.4.3)

Gemini 2.0 Pro experimental model taken offline

Gemini 2.0 Pro experimental model in AI Studio is gone. According to L Site users, currently still kept in Vertex AI, but my testing found Vertex AI’s Gemini 2.0 Pro experimental version showed chain-of-thought, probably replaced by Gemini 2.5 Pro experimental version—name might temporarily remain.

via: https://ai.google.dev/gemini-api/docs/models#gemini-2.5-pro-exp-03-25

Short-lived Gemini 2.0 Pro experimental version. Future GPT-5, Gemini 2.5 Pro [probably releasing around late May at Google I/O developer conference, possibly OpenAI will again race with Google] will likely be models combining reasoning and classic LLM, no longer requiring manual switching. If encountering questions not needing reasoning, use classic LLM for reply; if encountering reasoning scenarios, enable chain-of-thought.

Gemini 2.5 Pro VS Claude 3.7 Sonnet

Meanwhile, while organizing some bookmarked pages today, found a Hacker News post—Gemini 2.5 Pro vs. Claude 3.7 Sonnet: Coding Comparison. The linked article shows Gemini 2.5 Pro and Claude 3.7 Sonnet each have strengths, but overall Gemini 2.5 Pro is more cost-effective.

There were too many comments to review manually, so I asked ChatGPT Deep Research to analyze them. The report was published on my Halo Blog, but that copy is now offline; refer to the original Hacker News discussion linked above.

Gemini Code

Found a Gemini Code project inspired by Claude Code: https://blossom-tarsier-434.notion.site/Gemini-Code-1c6c13716ff180db86a0c7f4b2da13ab

Update (2025.4.2)

Deep use of Gemini App—experience is indeed good. Code comments written are nice, daily Q&A is sufficient.

But recommend asking in English as much as possible, especially when Gemini needs to call search tools. I found when asking in Chinese involving search, Gemini often simulates searching but doesn’t actually search. Friends not proficient in English can pair with Immersive Translate extension: triple-space to convert questions to English + translate English webpage to Chinese.

Update (2025.4.1)

Right after OpenAI’s Sam announced GPT-4o native text-to-image open to all users, Google’s Sundar Pichai announced Gemini 2.5 Pro Canvas open to all users. via: https://x.com/sundarpichai/status/1906874604683137285

First half of year’s most intense LLM battle has begun. April, May, June will be interesting. I feel Google’s Gemini model will impact RAG research—context window is large and attention decay is far less than other models.

Update (2025.3.31)

Before sleeping last night, remembered a benchmark proving Gemini 2.5 Pro context capability. via: https://fiction.live/stories/Fiction-liveBench-Mar-25-2025/oQdzQvKHw8JyXbN87

Can see Gemini 2.5 Pro’s article analysis in Gemini App—Gemini 2.5 Pro maintains very high understanding accuracy in long context.

Introduction

At midnight Beijing time on March 26, 2025, Google released Gemini 2.5 Pro model¹. Only a little over a month since my last Gemini blog post—can’t help but marvel at LLM iteration speed.

Gemini 2.5 Pro leads by far on various leaderboards. After these days hearing influencers’ praise, netizens’ reviews, and my own experience, I personally feel this model indeed has strength. Can say Google’s leading advantage in the 2025 LLM battle is beginning to show.

Google took down gemini-2.0-pro-exp-02-05 model in AI Studio to push Gemini 2.5 Pro—currently only callable via API.

Today Google directly opened Gemini 2.5 Pro in Gemini App to all users.

Current differences between free users and Gemini Advanced users:

Lacking Gemini 2.5 Pro Canvas feature
Rate limited [e.g., Deep Research free users have 10/month quota]
Context window limited

Google’s moves help acquire users faster while showcasing latest LLM progress.

Also freeloading users’ conversations to further improve Gemini model. When 2.5 Pro reaches GA (General Availability, official release), capability will probably level up again.

Personal Experience

Initially on the night of the 25th before sleeping, learned from overseas leak tweets that Gemini 2.5 Pro appeared in Gemini App.

Next morning, what first attracted me was actually OpenAI’s GPT-4o native text-to-image capability. After watching OpenAI’s Livestream, it indeed felt like the video said: Feel The AGI.

Can’t help but sigh: OpenAI is truly petty, always timing releases with Google, once again stealing some Gemini hype. GPT-4o’s native text-to-image is indeed impressive—everyone who used it says it’s good. Looking forward to May’s GPT-5 release vs Gemini 2.5 Pro official release showdown.

Initially, because Gemini 2.5 Pro is a reasoning model, I didn’t pay much attention. My daily reasoning model usage is limited: using OpenAI’s o3-mini-high for code comments; math-related questions, asking Yuanbao’s DeepSeek R1 [Thinking King—DeepSeek R1’s math ability is indeed impressive, more suitable for Chinese users, some math problems only DeepSeek R1 can answer accurately]; occasionally using Claude 3.7 Sonnet Thinking for problems Claude 3.7 Sonnet can’t solve.

Don’t underestimate Gemini 2.5 Pro in Gemini App—after all, App’s Gemini 2.5 Pro can use Browse, Youtube and other tools. AI Studio’s Grounding With Google Search is far inferior, even though Gemini App models may be chat-optimized versions with some poor UX aspects.

When I ask Gemini daily, I send questions to both Advanced and AI Studio, comparing and adopting the better answer.

Below shows Gemini 2.5 Pro model summarizing my Gemini 2.0 experience blog post. Gemini App model summarized the article via Browse tool, while AI Studio model lacking this tool failed to summarize.

If tools aren’t needed, can prioritize AI Studio models. Of course both places now offer Gemini 2.5 Pro free—can compare, not every question is answered better in AI Studio.

Gemini’s political sensitivity in Gemini App seems to be decreasing. Originally for sensitive topics like US President it would refuse to discuss. Now can get correct answers via external tool retrieval. Summarizing YouTube political videos—sometimes fails, sometimes succeeds.

Gemini 2.5 Pro’s knowledge cutoff reached January 2025—should be the most current knowledge cutoff of any LLM.

Other advantages: OCR, multimodal, longest context window, output token limits, etc.—see Simon Willison’s review article².

What I’ve Seen and Heard

KCORES LLM Arena claims Gemini 2.5 Pro is currently the best coding LLM.

Some foreigner had Gemini 2.5 Pro play Pokemon. Twitch livestream link: https://www.twitch.tv/gemini_plays_pokemon

Many LLM leaderboards currently show Gemini 2.5 Pro at the top.

Summary

For coding—who’s stronger between Gemini 2.5 Pro and Claude 3.7 Sonnet—only experiencing yourself gives answers. I personally think Claude 3.7 Sonnet might be better since I’ve trusted Claude since Claude 3.5 Sonnet. The only one letting me confidently Vibe Code, running LLM-generated code directly, is Claude—others fall somewhat short.

Once dependent on Claude, it’s really hard to break away. Though LLM development is rapid—yesterday’s darling might become today’s abandoned child—I’ll always reserve a spot for Claude. Won’t abandon it unless a truly Claude-replacing LLM appears. Gemini 2.5 Pro probably isn’t that replacement. In my mind, Claude’s coding and writing abilities are both number one.

After Gemini 2.5 Pro came out, my Grok3 usage dropped. Only use Grok3 when comparing Deep Search or linking X queries. Most other daily conversations prioritize Gemini 2.5 Pro.

Phind VS Devv

Tue, 25 Mar 2025 14:21:17 +0800

Update (2025.3.25)

Having Claude Pro doesn’t make Devv redundant. For programming questions requiring internet search, I usually ask Devv directly. Devv searches the internet paired with Claude 3.7 Sonnet Thinking model to help me.

Devv experience is really good. Recommend friends with budget who can’t get Claude Pro but want Claude models to subscribe. My afternoon writing might have been a bit biased. Devv renewal might continue next month, but Phind membership is cancelled.

Background Story

At the end of February, I subscribed to Phind. After that, I also subscribed to Devv. After nearly a month of use, sharing my personal experience with both.

Price-wise, Phind has no student discount—$20/month. Devv has student discount—after email verification with student ID, 20% off—$16/month.

I was willing to try Phind because I encountered a Huggingface TRL library issue, and among various AI searches, only Phind’s free 70B model found the solution from GitHub Issues through search.

Though if I manually searched, I probably could find the solution after some browsing. But this good experience promoted my later paid attempt.

First time trying Phind was during the GPT-4 explosion in 2023. Phind marketed itself as a programmer search engine. Back then Phind combined GPT-4 with web search—provided lots of help for my programming learning. I remember my old Windows computer’s Edge browser homepage was even set to Phind.

In 2024, I didn’t pay much attention to Phind. In February 2025, a Hacker News post—Phind 2: AI search with visual answers and multi-step reasoning caught my interest. Phind 2 released, officially claiming to reshape AI search with visual answers and multi-step reasoning. Saw the official blog—was tempted but held back.

Devv, this AI programming search, I registered or bookmarked in late 2023—URL is in my bookmarks but never used seriously. This is a Chinese developer’s overseas AI programming search. Saw V2EX and other platform users’ reviews—all praised Devv’s user experience.

Both AI programming searches initially offered free GPT-4+web search. After attracting users with free strategy, commercial attempts began. Free is unsustainable—especially with expensive frontier model API prices. But commercialization inevitably loses some users. After late 2024, basically no more user experience shares for these two.

Phind

Pro membership claimed features:

Unlimited Phind series model searches
Multi-query search mode
Analyze images, PDFs, CSVs
500 daily GPT-4o, Claude 3.7 Sonnet, 10 Claude Opus
Chat data opt-out training option
Run code in browser

Cons

Phind 2’s claimed visual search only supports Phind series models. GPT, Claude series don’t support.

When I subscribed, it was right before Claude 3.7 Sonnet release. Initially chose Claude 3.5 Sonnet, searched a few times and found no visualization effects. Switched to Phind series—visualization appeared.

Phind 2.0 only supports image upload for Phind series models. GPT, Claude series don’t support.

I specifically asked in Phind Discord group. Reply: Phind 2.0 only supports image upload for Phind series models.

No image upload support seriously limits my expression. This month’s experience was truly frustrating.

Phind series models are weak

Based on Llama 3.1 series fine-tuning. Those who know, know. Meta’s open-source model experience isn’t great—even foreigners abandoned Llama in 2024, embracing Qwen.

Zuckerberg watching you use Qwen instead of LLaMA. 😁

Running code in browser—testing showed only Phind series models support it. Really weak.

Chinese questions search Chinese internet

I modified Answer Profile prompts and asked everything in English—barely got some experience.

Claude 3.7 Sonnet has no Thinking mode—only regular mode. Not all problems need Thinking, but Thinking mode should exist.
Limited context

Estimated 32K context window. Someone in Phind Discord group shared expectations for Phind development—shows current Phind is declining.

Seeing foreigners’ crazy obsession with uncensored DeepSeek R1 makes me laugh. Want less censorship—just use Grok. Musk’s model has least censorship. Wanting open-source models with less censorship is impossible—every country has its stance and situation. Open-sourcing relatively completely already shows enough sincerity.

Pros

Seems no pros. Even if Claude and GPT models are authentic with many daily uses—experience is just marginal. Phind 2 years ago with internet connection had some advantage, but now with all major LLM providers integrating search—Phind is truly worthless now, though the 70B model once gave me a glimmer of light.

Other

Phind supports image generation, video generation—probably using open-source solutions. AI programming search with these fancy features is totally unnecessary.

Video generation link: https://www.phind.com/search/cm8k4gno200003b6syi9uwty5

Phind reportedly has VS Code extension—too lazy to install and try. Current AI programming extensions pale compared to Cursor, Windsurf.

In Phind’s Discord group, I even encountered BLM. Speechless.

Supplementary case—showing Hacker News latest

At that time [March 12, 2025 afternoon] I tested many models—only Phind and GPT search could get Hacker News top Gemma3 release discussion. ChatGPT still has strength—user experience is well done. Didn’t try Claude with MCP to fetch Hacker News.

With different prompts, Devv can also fetch Gemma3 release discussion.

Recently Claude launched search—unfortunately integrated Brave Search. Brave Search quality definitely isn’t as good as Google Search. For this case, prompts failed—couldn’t get real-time Hacker News info, searched content from days ago.

Tried March 25, 2025 afternoon—Claude 3.7 Sonnet Thinking still can’t properly show Hacker News real-time info? Point is: Brave Search is weak. Really hope Anthropic finds a better search engine partner.

I admit Anthropic adding search to Claude improved capabilities, but must point out existing flaws. Sometimes I sigh—Claude’s strongest form should be Claude Desktop+MCP Google Search/Kagi Search/SearXNG/other high-quality search engines.

Summary

Phind iteration is too slow. Phind 2’s claimed visual search just uses web-scraped images and Mermaid code for charts and flowcharts—such visual search is too basic. Promotion vs actual experience gap is too big.

I definitely won’t renew. This month’s membership fee was paid with dollars from selling VPS traffic—doesn’t hurt.

Devv

Compared to Phind, Devv has more merits.

Pro membership claimed features:

Unlimited search
Advanced model access
Search and GitHub mode support
Unlimited advanced model access
Image upload support (max 4 images at once, 50 daily image searches)
Extended memory context
36K input window

Cons

36K input window

With membership, single input limit is 36000—can’t compare to Claude official site.

GitHub mode model can only see part of repository content.

Would be better if it could see entire repository, then query relevant files based on user questions and explain corresponding code.

During this month’s trial, I basically never used this mode. Adding personal repo needs time for Devv to index.

Not general search

General question search not as good as Perplexity—can’t really call it a con since they market as developer search engine.

Sometimes has hallucinations

Current Devv’s Claude 3.7 Sonnet is the Thinking version, but not all problems need thinking.

Even with thinking, sometimes has hallucinations—can be misled by web info.

Remember once asking Devv’s Claude 3.7 Sonnet about Ollama config—result had wrong info.

Pros

After setting user preferred language, can ask in Chinese, search in English, reply in Chinese.

Devv Contexts

Devv Contexts lets developers select and include programming languages, platforms, tools, libraries, and frameworks for focused accurate search results.

Actually I rarely use @ symbol to limit scope. Devv’s model is definitely authentic—created HTML page truly has Claude’s aesthetics!

Unlimited advanced model access

This is more generous. Average person probably maxes at 50 questions/day. Vendors know normal people can’t ask many questions—unlimited isn’t really a loss.

Think about it—average user asks at most 10 questions/day, nearly 300 questions/month. Claude API probably can’t spend $20. Unless constantly chatting in one conversation, rapidly consuming tokens—$20 definitely can’t be used up.

Web search toggle

Phind etc. also have toggles—turning off search means using advanced models with limited context and input length.

Devv with web search has Devv Agent planning; without web search, it’s authentic LLM models.

Paired with Claude 3.7 Sonnet Thinking—good experience.

Summary

Don’t think less space on Devv review means I didn’t care—actually Phind just has too many complaints.

Devv author’s experience sharing posts on V2EX, X are worth reading.

For users who can’t subscribe to Claude Pro—paying for Devv is a good choice.

The referral that gave each party a $10 credit for the Devv service reviewed here has expired; this archived referral page preserves the original offer.

For Claude Pro users—paying for Devv is slightly redundant. Claude official experience is already quite good. Though Brave Search is sometimes lacking, most of the time the boost to Claude is obvious.

Yesterday I discovered another point where Anthropic leads others: can search even with attachments!

Summary

Claude official site is the one true god. Devv is decent. Phind currently looks like a defective product.

Claude 3.7 Sonnet Experience

Tue, 25 Feb 2025 07:55:29 +0800

Update (2025.7.23)

Claude Code is no longer a toy. With the Claude 4 series models online, Max membership paired with Opus 4 model is just too good. Those who know, know—the strongest AI programming tool!!! In just 1-2 months, successfully turned Cursor from sweetheart to has-been. Only Anthropic entering the arena could do this.

Update (2025.4.29)

Don’t underestimate Claude. Currently Gemini 2.5 Pro, o3 are indeed impressive, but I still haven’t abandoned Claude for programming and writing. For polishing article expression, I still prefer Claude [premise: the text to polish has been roughly expressed clearly, minor details might read awkwardly, then using Claude for polishing definitely achieves excellent results].

via: https://x.com/alexalbert__/status/1916878483390869612

Update (2025.4.20)

Can’t fully embrace Claude either, but can’t underestimate Claude. Current LLMs are truly dazzling—sometimes don’t know which model to use. Because I personally have strong Claude inertia, yesterday I wrote Claude-praising content, but recent Gemini 2.5 Pro, ChatGPT o3, o4-mini series updates are also really top—all SOTA. Having choice paralysis.

Update (2025.4.19)

Whenever I learn new knowledge, I still first consider Claude. Gemini 2.5 Pro can’t achieve Claude’s rich yet not overly verbose communication experience. Claude sometimes has excellent generalization (so-called soul)—incisive replies to questions feel surprising yet expected. Though I compare all current LLMs, overall after getting used to Claude’s reply style, so far no LLM catches my eye. No matter how Gemini 2.5 Pro, o3, o4-mini-high dominate benchmarks, my heart always belongs to Claude.

Update (2025.3.25)

Productivity still needs ChatGPT and Claude. The “OpenAI is dead” statement in the article was purely joking. For code comments, I still prefer OpenAI’s o3-mini-high model. Plus the newly released GPT-4.5 has better replies for some concept explanations.

Update (2025.3.21)

Claude supports Web Search now. via: Anthropic’s announcement.

Probably a big blow to AI search wrapper market. I previously used Perplexity and other AI searches mainly because they support Claude model.

These AI search wrappers might have advantages over Claude native search in some areas. Compare and use both to better understand their pros and cons.

Update (2025.3.1)

Recommend prioritizing Normal mode. Extended thinking mode only when Normal can’t solve. Reasoning models excel at: math, coding, logic. In other areas, reasoning models can’t beat classic LLMs. For example, having Claude write—Extended mode definitely performs worse, less creative text than Normal mode. Same logic for other LLMs—prioritize classic LLM, only consider reasoning models when classic LLM can’t solve.

Programming ability is absolutely far ahead. Had Claude 3.7 Sonnet write a script calling MinerU’s API to implement PDF-to-Markdown—done in just a few conversation rounds! Error analysis, Artifact Making Edits, etc.—just too impressive! Enjoying Vibe Coding.

Update (2025.2.26)

Claude Code is totally a toy. Yesterday saw a blogger use Claude Code to add new Features to their project. I don’t have good ideas either—randomly had Claude Code make a Hungry Bear. Natural language programming took over 1 hour—feels inferior to Cursor, Windsurf and other AI editors. Still need to learn programming properly. Natural language programming process is extremely difficult. The more tech you know, plus Claude assistance, the better you can hit targets!

Anthropic official Twitch livestream of Claude playing Pokemon: https://www.twitch.tv/claudeplayspokemon

Update (2025.2.25)

Netizen comment: “If you know coding, Claude will make you a coding god!”

Another case update: generating Gomoku game

Played several rounds, never could win. Claude 3.7 Sonnet Thinking-designed game is impressive!

via: https://claude.site/artifacts/16727408-f553-41da-aaa5-bbb27e47301d

February 24, 2025 [February 25, 2025 Beijing time midnight] Claude 3.7 Sonnet emerged—the true far-ahead arrived on earth!

Update Content

First look at official News main content¹. This time chose Phind’s Claude 3.7 Sonnet for summarizing.

After carefully reading the News, feeling was shock!

My question: Official News claims Claude 3.7 Sonnet is the market’s first hybrid reasoning model?

Phind and Grok3 DeepSearch thoughts:

Personally lean toward thinking first hybrid reasoning model should be Grok3—after all, clicking Think button makes Grok3 think before replying. DeepSeek and others’ reasoning models are new models. Maybe my understanding is wrong since this view is still controversial.

Official research blog—Claude’s extended thinking², Phind summary:

Differences from previous reasoning models:

Claude 3.7 System Card³, Claude 3.7 Sonnet Extended summary:

GitHub Integration⁴

Select files/folders directly to add corresponding content to Chat. If a GitHub project is critical for your business but code is hard to understand, or code needs new features, can add corresponding code parts to Claude Chat this way and have Claude strategize! Tested—private repos work too, provided Claude For Github App has read permissions for relevant repos.

But thinking carefully—my blog content folder is 400+ KB, already occupying 62% of capacity limit. And in one conversation, can’t add more GitHub files—only at initial stage. Still somewhat limited. Plus it only gives text explanations or hints for code—can’t operate the code. For this, still need Cursor, Windsurf and other AI code editors for better global perception and editing.

Claude Code⁵

Phind summary:

Recommend pairing with VSCode-type editor, using remote SSH to connect to US clean IP Linux VPS for development experience. Personally feel this is still a toy like Computer Use. Money Is All You Need! Claude’s API pricing is higher than other LLMs, but results are really good.

# Download and install fnm (Fast Node Manager)
curl -fsSL https://fnm.vercel.app/install | bash
# Reload bash config to make fnm command available
source ~/.bashrc
# Install Node.js version 22.14.0
fnm install 22.14.0
# Set Node.js version 22.14.0 as current version
fnm use v22.14.0
# Globally install latest pnpm 10.x version
npm install -g pnpm@latest-10
# Set up pnpm config
pnpm setup
# Reload bash config again to make pnpm command available
source ~/.bashrc
# Globally install Claude Code CLI tool
pnpm add -g @anthropic-ai/claude-code
# Create a new directory named claude-test-snake-game-in-terminal
mkdir claude-test-snake-game-in-terminal
# Enter the newly created directory
cd claude-test-snake-game-in-terminal
# Start Claude Code CLI tool
claude

Claude Code currently at full capacity—will try when spots open.

Reportedly has Easter egg. Stickers only ship within US.

via: https://x.com/nrehiew_/status/1894112547873210710

thinking budget

API users can precisely control model thinking depth via thinking parameter. Similar to OpenAI o series’ reasoning_effort. DeepSeek docs also mentioned upcoming reasoning_effort parameter. Today found DeepSeek recharge channel restored—topped up 50 yuan while writing, just in case.

Reduced unnecessary refusals

I mainly ask code and learning questions—basically never encountered refusal operations.

via: https://x.com/AnthropicAI/status/1894095494969741358

New model, pricing same as previous Sonnet version

Expensive, but excellent results!

Chain-of-thought made public

Claude 3.7 Sonnet Extended chain-of-thought is collapsed by default.

Currently DeepSeek, Qwen, etc. default to expanded state. Foreign ChatGPT o series, Grok3, Gemini Flash Thinking model, Claude 3.7 Sonnet chain-of-thought all default collapsed. Both interaction methods are OK—no better or worse.

Reportedly harmful content in chain-of-thought not shown to users.

Coding and frontend web development far ahead

I won’t elaborate—seeing X discussions, all Claude code ability crushing other models posts. Personally predict coding ability definitely improved further—after all, previous version was already code king among classic LLMs. Indeed, only Claude can surpass Claude non-reasoning models.

Looking at livebench.ai rankings, this Sonnet version’s code ability evaluation improved but not much. Don’t be fooled by o3-mini-high’s high code scores—real user experience is still Claude. OpenAI’s o3-mini series proves: “Never lost on benchmarks, never won on user experience!”

Note: livebench.ai considering all evaluation metrics, Claude 3.7 Sonnet Thinking now tops! After writing blog, checked website and found updated rankings!

Experience the following tweet yourself—Claude series models absolutely far ahead! OpenAI’s o series models are just little brothers.

Source: @cline on X (the original post is no longer available; its screenshot is preserved above).

Now look at Phind’s Claude 3.7 Sonnet analysis of aider leaderboard. Simply terrifying—too strong!

Saw bloggers say its writing ability declined—didn’t test specifically, currently no writing task scenarios.

As long as LLM has one top-tier aspect, no shortage of users. Don’t expect LLMs to be all-around. Generally LLM capabilities are trade-offs—training data with more code data might weaken writing ability.

Discovered Improvements

Code comments better follow instructions compared to October’s Sonnet.

This Claude version’s code comments, whether Normal or Extended, can follow instructions to add comments above each line. Previous Sonnet version pursued minimalist beauty—less is more. My preference is more comments the better—easier to understand.

Interesting Cases

Who is the current US President?

Anthropic’s survival instinct is strong.

Strawberry puzzle

Claude 3.7 Sonnet Normal/Extended both use frontend code to display for strawberry puzzle:

Normal:

Extended:

In my testing, Normal’s frontend page was better!

Rotating ball test

Normal:

via: https://claude.ai/share/13475764-f78e-4b1b-8be7-9fb438cd540e

Extended:

Saw netizen on X say Claude 3.7 Sonnet Extended can’t pass rotating ball test—my test passed.

via: https://claude.ai/share/c5d2f51a-6907-43e7-838e-553b04818de1

Pygame online test page: archived copy (the live page is unavailable)

Letter count test

Normal:

Extended:

Personal subjective feeling—in this test Normal mode answered more comprehensively. Thinking more doesn’t mean better answers. I tested Grok3 Thinking with this question—thinking 3s gave comprehensive answer too, while thinking 17s gave answer similar to Claude 3.7 Sonnet Extended.

Promising Future Points

Web search

Days ago there was leak about Claude integrating web search—didn’t launch today as expected. If Claude truly integrates Web search and optimizes the experience—like fetching accurate solutions from GitHub project Issues—this would be a dimension-crushing blow to current AI searches. Currently Perplexity, Phind and such AI searches can more accurately fetch solutions for code error messages compared to ChatGPT Search, Gemini Google Search, Grok3 DeepSearch.

Summary

OpenAI can be said to be dead. After reading all Claude release content this morning, felt Anthropic will approach AGI faster! Reportedly OpenAI releasing GPT4.5 this week. If released model can’t beat Claude 3.7 Sonnet Normal, probably really close to death. The PDF document released days ago containing telemetry analysis of Chinese users’ ChatGPT behavior—now I can only remote US Windows with US residential IP to compare OpenAI products [local phone, computer, tablet ChatGPT apps all uninstalled].

OpenAI, Anthropic products can only be used via remote US Windows computer with US residential IP—local usage security too low. Dumbing down, account bans—these operations are frustrating!

Also don’t forget Anthropic’s Citation feature released last month—this feature provides significant value for RAG applications.

Though recently Anthropic CEO released controversial statements, I feel their products are truly the most resilient. Remember someone unsubscribed from Claude Pro because they couldn’t stand his ugly face—I think it’s not worth it. This would make you miss using the most powerful AI tool. For regular people, support whichever company’s product is excellent—everything else is irrelevant to me!

From the simple cases earlier, not all questions are better with Extended mode. Normal, Extended two modes each have strengths. Try different modes to find the best Claude 3.7 Sonnet reply for certain questions.

Looking forward to Anthropic’s future web search and Claude4! Predicted similar to last year’s release timeline—next release around late June!

Supplement

One conversation window can only be locked to one Claude 3.7 Sonnet mode—can’t switch different models in one conversation window like ChatGPT.

via: https://mp.weixin.qq.com/s/MedDDltDvKWp1uJTGF9yPg

Gemini 2.0 Experience

Fri, 07 Feb 2025 09:01:24 +0800

Update (2025.3.26)

Gemini 2.5 Pro is out. After watching some blogger reviews, impressed that Gemini OCR ability has improved even more.

Update (2025.3.19)

Last night, Gemini App updated again. via: https://blog.google/products/gemini/gemini-collaboration-features/

Canvas

Similar to Claude Artifacts, ChatGPT Canvas. ChatGPT’s Canvas started supporting code rendering in January this year.

Audio Overview

Added NotebookLM’s Audio Overview feature to Gemini—still only supports English podcasts as always.

Must complain—why is Gemini 2.0 Pro still Exp? Flash model with more new features still isn’t competitive! Expect 2.0 Pro to shed its Exp coat in May.

Update (2025.3.14)

Last night Gemini App updated Deep Research [free users’ quota changed from 5/month to 10/month], replacing model from 1.5 Pro to 2.0 Flash Thinking Experimental. Non-Advanced users can use it too. Currently Advanced users only have one more option than free users: 2.0 Pro Experimental—increasingly marginal.

Gemini series models can indeed be completely free—after all, AI Studio’s 2.0 Pro Experimental now supports YouTube video summarization too, while Gemini App’s 2.0 Pro Experimental still can’t connect to YouTube.

Gemini users can try Deep Research a few times a month at no cost. Completely free—same logic as Grok, register multiple accounts and it’s definitely enough.

Update (2025.3.13)

Google AI Studio added YouTube video support.

Feels like native video understanding ability, not implemented through YouTube subtitles.

YouTube videos without subtitles can also be roughly understood.

Sometimes I wonder if Gemini understands YouTube videos through subtitles or pure native video understanding. Key point—this video has no subtitles at all. Anyway YouTube belongs to Google ecosystem—summarizing videos is a piece of cake. Note: According to Logan who manages AI Studio, it’s native video understanding. Native Video Understanding!

Videos without subtitles—Monica can also summarize.

Meanwhile, Gemini 2.0 Flash Experimental added native image output! True multimodal!

Native Image Output!

Update (2025.3.1)

Gemini video summary gives rough overview. 2.0 Flash is more stable—reasoning models may have issues like Russian output, not auto-calling YouTube extension.

At midnight Beijing time on February 6, 2025, Gemini 2.0 released new updates¹.

Gemini App

Gemini 2.0 Flash went live on API. Gemini 2.0 Flash went live in App at midnight Beijing time on January 31, 2025.

Based on these days’ experience, Gemini 2.0 Flash in App for YouTube video summarization feels like restrictions are increasing—safety is more aggressive now. Of course healthy, non-Trump, subtitled videos can basically be summarized.

With yesterday’s update, for me, the main model for summarizing YouTube videos is no longer 2.0 Flash or 1.5 series—should choose 2.0 Flash Thinking Experimental with apps [reasoning model that can connect to YouTube, Google Maps, Google Search].

Its video summaries are more detailed. For just getting video overview, can choose Gemini 2.0 Flash or 1.5 Pro.

Other App models can be ignored—after all, these models are chat-optimized, losing performance. Using Gemini models without connecting to Google suite services—prioritize freeloading AI Studio models.

Currently Gemini Advanced has 2.0 Pro Experimental, 1.5 Pro with Deep Research, 1.5 Pro over non-members—marginal.

Encourage everyone to use Gemini App to summarize YouTube videos, call Imagen3 text-to-image in Gemini App—free version is enough.

Imagen3 is reportedly strong in drawing and is now on Gemini API². Paid API generates one image for $0.03, while calling in Gemini App is completely free.

Gemini API

For freeloading in AI Studio, prioritize gemini-2.0-pro-exp-02-05 model.

For API work usage [like calling API to batch remove HTML elements from webpages, keeping text], definitely consider Flash series. According to Google’s official blog³, 2.0 Flash series improved performance while keeping original prices. 2.0 Flash removed 1.5 Flash’s tiered pricing. To further reduce costs, consider Gemini 2.0 Flash-Lite model.

Note that Gemini 2.0 Flash-Lite supports multimodal input but only text output.

Leaderboards and Experience

Though leaderboards have some distortion, rankings roughly estimate model capabilities. Prioritize livebench leaderboard—Gemini 2.0 series models aren’t as impressive as imagined. Experimental model evolution brings some capability improvements and some declines—not all capability metrics improved.

Currently o3-mini-2025-01-31-high reached cliff-leading 80+ in coding, but truly useful in developers’ minds is still claude-3-5-sonnet-20241022. The classic non-reasoning LLM that can surpass Claude—looks like only Claude itself.

Claude excels not just in coding—text abilities are also great. Chatting with it feels more like a real person—its output text has more warmth compared to other LLMs, though sometimes lazy. Setting aside CEO Dario Amodei’s controversial blog posts, Claude is truly amazing!

My daily learning priority is always Claude. Besides Claude Pro, I recently subscribed to Windsurf Pro—Cascade AI agent has good user experience and lower cost than Cursor’s $20/month.

Personal Thoughts

Gemini series models, my use cases:

App summarizing YouTube videos

Gemini App for me is mainly summarizing YouTube videos. Unless video is compelling enough or hands-on type, I prefer using Gemini to summarize and save time.

Flash series in production

Processing data in production—use Flash models for best cost-effectiveness. Recently saw a blog post “Ingesting Millions of PDFs and why Gemini 2.0 Changes Everything”⁴ ⁵—author notes Gemini 2.0 Flash excels in cost-effectiveness, OCR accuracy is near-perfect and cheap.

Using Flash model to summarize web articles in Glarity Chrome extension

Daily Page Summary usage is 10-20 times. Monthly cost is very low—January 2025 Gemini API GCP bill was $0.06.

Though many free webpage summarizing extensions exist, I still prefer Gemini Flash series—after all, large context window and low cost.

Gemini claims large context window. Using Gemini this long, I’ve never had a conversation exceed the window—can’t comment on this. Large context window theoretically benefits RAG, but actually larger window isn’t always better—more content means more noise.

Gemini models have strong visual ability. Last semester I used Gemini to extract Chinese characters from news images. An image crammed with multiple news items—Gemini recognized almost all Chinese characters. Multimodal ability is indeed strong.

When Project Astro officially launches, expect more surprises.

Summary

Gemini models currently have merits. Compare with other models regularly to better discover strengths and weaknesses. Google series’ strength is excellent integration with its suite—ecosystem is uniquely Gemini’s.

Gemini is definitely an underrated model. Don’t ignore its gradual improvement in 2024, 2025 because of Google Bard’s struggles in 2023. Renaming from Bard to Gemini was a successful rebrand attempting to shed Bard’s negative image—Gemini series updates have indeed proven Google’s strength.

Facing DeepSeek’s current explosion, you might ask—don’t you use DeepSeek daily?

Personally I think DeepSeek has substance, but doesn’t mean it’s invincible, completely achieving East rising West falling! Can only say open-source approaching closed-source⁶. For example, DeepSeek currently lacks multimodal—real-time voice lags behind Doubao and other models.

Plus DeepSeek’s recent explosion overloaded its service. If just calling R1 API, feels lacking. R1+search achieves best DeepSeek experience. Will add to my daily LLM options after DeepSeek service stabilizes—otherwise asking one question then getting server busy really affects experience.