GLM-5.2 Hands-On Review: Another New Peak for Domestic Coding Models

The surreal nature of the world these days is truly disheartening.

This morning, Anthropic received a letter from the U.S. Department of Commerce.

The letter was simple: citing national security concerns, it demanded that Anthropic immediately suspend all access to Fable 5 and Mythos 5 for foreign citizens — not just users outside the U.S., but also foreign citizens within the U.S., including Anthropic’s own foreign employees.

Then Anthropic made a decision no one expected: to ensure compliance, they shut down Fable 5 and Mythos 5 for all users — even Americans couldn’t use them anymore.

It exploded on X with 50 million reads.

This caused a massive uproar; the entire internet blew up.

When I woke up from my nap and saw the news, my heart sank. Because when it comes to pure code execution, I think Opus 4.8 and GPT 5.5 could also handle the job. But Claude Fable 5’s ability to build solutions, architect systems, and produce complete, comprehensive output is unmatched by any model. I had just used it to help me optimize the AIHOT selection algorithm, and to fully adapt and refactor for mobile. I was about to start developing the mini-program today, and then it was gone…

Just 4 days, and this model, hailed as the strongest in the world, was recalled and fully taken offline.

And then, in the context of this World Cup emphasizing global unity, a Somali World Cup referee was denied entry to the U.S. and missed the tournament.

The world’s landscape seems increasingly different.

It also seems increasingly closed.

As we were feeling dejected watching all this unfold…

At 2:19 PM, Zhipu suddenly published an announcement.

“At a time when some frontier models suddenly become unavailable, we choose to believe in another path: frontier intelligence should not belong only to a few, nor should it be revoked at any moment by a few rules. It should be open, available, buildable, and serve every developer.”

My feed was instantly flooded.

And this time, GLM 5.2 continues to be open-source.

I don’t need to reiterate how well GLM 5.1 is regarded in tech and AI circles — it’s basically recognized as a domestic pride, one of the few models that can hold its own against Claude and GPT. In Coding and Agent capabilities, it’s also the model I recommend first to all my friends who can’t use overseas models.

If it weren’t for compute constraints — there are almost no GPUs in China, both for training and inference, orders of magnitude less than abroad — I truly believe that companies like Zhipu and DeepSeek could absolutely build models no less than those two overseas companies.

This time, the announcement took me by surprise. I was even out eating when I saw it. I pushed back my afternoon plans, rushed home, and luckily my Coding Plan was still active, so I got access to GLM 5.2.

Let me explain: today GLM 5.2 is launched via Zhipu’s Coding Plan. You can think of Coding Plan as a subscription like Claude or GPT — only subscribed users can use it.

Next week, API access will be available, and it will be open-sourced directly.

And the timing of their release at 5:21 PM today is quite ironic.

Because Anthropic received the letter at 5:21, so Zhipu chose to open access at 5:21.

One side is closing doors, the other is opening them.

One side says frontier intelligence is a national security risk, the other says frontier intelligence belongs to everyone.

Honestly, it’s hilarious — the drama is maxed out.

The annoying thing about Coding Plan is that they have very limited compute resources — they can’t support inference requests from all users. So Coding Plan is quota-limited, meaning you have to scramble to buy it…

So if you want to use it, set an alarm for 10 AM every day and try to grab a slot.

After testing it myself and discussing with some friends, I want to say: this is a new peak for domestic models. At least in my view — apart from the slowness due to compute constraints — in terms of pure results, as long as you’re not doing heavily design-oriented tasks, GLM 5.2 tasks aren’t that far behind Opus 4.8.

In large projects, long tasks, backend work, etc., it’s very strong — extremely strong.

I think the gap mainly lies in the sophistication and completeness of the initial plan, and design differences.

There are many strengths. The output of GLM 5.2 is understandable, I can reason with it, hallucinations are extremely low, it’s stable as a rock, and this time the context length has finally been extended to 1M, which is great.

During testing, at around 400-500k context length, accuracy and instruction following were not far off from Claude — very stable. My Claude.md file at 400K length also followed instructions fine. I usually like to manually save with my “cleanliness.skill” at that length. Beyond that, say 500k to 1M, I rarely go.

The biggest pity is that GLM 5.2 still doesn’t have multimodality — it’s still a pure text model.

As for work capability, no complaints. My assessment: it’s more like a diligent ox — it will get the job done well. Its intelligence certainly doesn’t match Claude Fable 5’s level, and it’s slightly behind Opus 4.8 in smarts, but it’s already very good.

For example, a small task on AIHOT today.

Recently, to aid my own learning and save some time, I used some interesting methods to monitor a few WeChat public accounts I follow, so I could get information instantly. But today I found a bug: I had monitored Zhipu’s public account, but the GLM 5.2 announcement at 2:19 PM didn’t get picked up by AIHOT. It wasn’t until 4 PM, when Zhipu posted on X, that I saw it.

That was strange. So I threw the problem at GLM 5.2 to try.

Actually, while it was solving it, I already had a rough idea of the cause. A while back I switched monitoring schemes, and now two schemes are running in parallel in a gray rollout. Chances are, one of the third-party API accounts we switched to ran out of funds. I meant to top it up the day before yesterday but got too busy.

But it was a good test — a small thing to gauge the model’s intelligence. My project is about 100,000 lines of code, with various monitoring and scheduling, so the backend logic is somewhat complex.

GLM 5.2 eventually found the issue. Basically, Zhipu hadn’t posted an article for several days — it had nothing to do with our scraping system…

Then it followed that trail and thought our entire monitoring system was bugged.

Finally, it found the answer.

Then it asked if I wanted to set up monitoring.

Total time: 21 minutes.

Claude Opus 4.8’s thought process was nearly identical to GLM 5.2. The only difference: in fast mode, it finished in 6 minutes; without fast mode, it’d normally take about 10 minutes.

So Claude Opus 4.8 was about twice as fast as GLM 5.2, but the process and result were exactly the same.

This is fundamentally an infrastructure and compute gap — an infrastructure issue.

Then I casually asked GLM 5.2 to handle the follow-up.

Because my documents and memory are extremely standardized, and I have a dedicated Feishu alert group that pushes notifications via Feishu bot. So I was confident GLM 5.2 could do it. The question was whether it could find the balance alert method fastest, locate my group, and get the job done.

Patch flow + check code/docs + develop + test + merge + update memory and docs with cleanliness.skill — perfectly done in 26 minutes.

Verified, no issues.

Then I gave it a slightly bigger task.

Directly convert AIHOT’s website into a mini-program. I had originally planned to use Fable 5 for this today, but since Fable 5 was gone, I used GLM 5.2 instead…

I just threw the mini-program’s development directory into the prompt, along with the mini-program development docs, and said: “Help me turn AIHOT into a mini-program version.”

After some research, GLM 5.2 asked me two questions.

I blindly clicked the first one.

Then it started listing a plan, and after the plan, it spun up 4 parallel Agents to start development.

In about 40 minutes, the mini-program was done.

No major bugs — everything was clickable, no errors, all required features and information present. But man, it was ugly = =

The bottom tab bar had a small bug — the background was missing, and the tab bar adaptation wasn’t done properly. I had to tweak it a bit.

But for other logic display, API calls, etc., there were almost no issues. GLM 5.2 is truly rock-solid for slightly larger tasks.

But to make it a fully polished mini-program, you’d definitely need to fine-tune the UI details. Compared to Claude — whether Fable or Opus — it’s still a bit less hassle-free.

I think the design/aesthetic gap will only see a qualitative leap when Zhipu adds multimodal capabilities.

Then I asked GLM 5.2 to use Three.js to build an online gamified camp we plan to launch for our community in the future. This was the result after one pass.

You can see stability is fine, but the aesthetics — it’s usable, but if you want beautiful and refined, there’s still some gap.

Skill construction is also an important aspect now. I tested it with the “clean computer” skill I created before.

I reconstructed it from scratch using only voice — the final feeling was basically no different from a Skill developed by Opus 4.8.

You can check the result.

In my limited time with it, GLM 5.2 overall was a pleasant surprise and exceeded my expectations.

As long as you exclude aesthetics and multimodality, in my experience, it can really compete with Opus 4.8.

At this point, I think two domestic models are extremely worthy of use.

For anything involving Agents and Coding, blindly recommend using GLM 5.2 + Claude Code framework — that’s the strongest combo you can get domestically right now.

For general knowledge tasks like planning, writing, etc., blindly recommend DeepSeek V4 Pro — I think it’s currently the best model for world knowledge.

At the end of today’s WeChat article, Zhipu wrote two lines in English.

A step closer to frontier intelligence for everyone.

The future of AI is open, and it is for the people.

I think these two sentences, in today’s context, are especially evocative.

The 2026 AI track is witnessing jaw-dropping events every day.

One side is building walls, the other is laying roads.

But I still firmly believe:

Under the surging tide, these walls will inevitably collapse.

Intelligence should be for everyone.

The new era will definitely arrive.