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GLM 5.1 is pretty good, probably the best non-US agentic coding model currently available. But both GLM 5.0 and 5.1 have had issues with availability and performance that makes them frustrating to use. Recently GLM 5.1 was also outputting garbage thinking traces for me, but that appears to be fixed now.
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Use them via DeepInfra instead of z.ai. No reliability issues.

https://deepinfra.com/zai-org/GLM-5.1

Looks like fp4 quantization now though? Last week was showing fp8. Hm..

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Deepinfra's implementation of it is not correct. Thinking is not preserved, and they're not responding to my submitted issue about it.

I also regularly experience Deepinfra slow to an absolute crawl - I've actually gotten more consistent performance from Z.ai.

I really liked Deepinfra but something doesn't seem right over there at the moment.

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Damn. Yeah, that sucks. I did play with it earlier again and it did seem to slow down.

It's frankly a bummer that there's not seemingly a better serving option for GLM 5.1 than z.AI, who seems to have reliability and cost issues.

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In fact it is appreciated that Qwen is comparing to a peer. I myself and several eng I know are trying GLM. It's legit. Definitely not the same as Codex or Opus, but cheaper and "good enough". I basically ask GLM to solve a program, walk away 10-15 minutes, and the problem is solved.
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cheaper is quite subjective, I just went to their pricing page [0] and cost saving compared to performance does not sell it well (again, personal opinion).

CC has a limited capacity for Opus, but fairly good for Sonnet. For Codex, never had issues about hitting my limits and I'm only a pro user.

https://z.ai/subscribe

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Yes. GLM 5.1 is that good. I don't think it is as good as Claude was in January or February of this year, but it is similar to how Claude runs now, perhaps better because I feel like it's performance is more consistent.
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GLM 5.1 is the first model I've found good enough to spring for a subscription for other than Claude and Codex.

It's not crushing Opus 4.5 in real-life use for me, but it's close enough to be near interchangeable with Sonnet for me for a lot of tasks, though some of the "savings" are eaten up by seemingly using more tokens for similar complexity tasks (I don't have enough data yet, but I've pushed ~500m tokens through it so far.

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I'm using GLM 5.1 for the last two weeks as a cheaper alternative to Sonnet, and it's great - probably somewhere between Sonnet and Opus. It's pretty slow though.
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This is what kills it for me… The long thinking blocks can make a simple task take 30 minutes.
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GLM-5 is good, like really good. Especially if you take pricing into consideration. I paid 7$ for 3 months. And I get more usage than CC.

They have difficulty supplying their users with capacity, but in an email they pointed out that they are aware of it. During peak hours, I experience degraded performance. But I am on their lowest tier subscription, so I understand if my demand is not prioritized during those hours.

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Where are you getting 3 months for $7?
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They had a Christmas deal that ended January 31.
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If you only look at open models, GLM 5.1 is the best performance you can get on on the Pareto distribution

https://arena.ai/leaderboard/text?viewBy=plot&license=open-s...

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I've been using it through OpenCode Go and it does seem decent in my limited experience. I haven't done anything which I could directly compare to Opus yet though.

I did give it one task which was more complex and I was quite impressed by. I had a local setup with Tiltdev, K3S and a pnpm monorepo which was failing to run the web application dev server; GLM correctly figured out that it was a container image build cache issue after inspecting the containers etc and corrected the Tiltfile and build setup.

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Most HN commenters seem to be a step behind the latest developments, and sometimes miss them entirely (Kimi K2.5 is one example). Not surprising as most people don't want to put in the effort to sift through the bullshit on Twitter to figure out the latest opinions. Many people here will still prefer the output of Opus 4.5/4.6/4.7, nowadays this mostly comes down to the aesthetic choices Anthropic has made.
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Not just aesthetics though, from time to time I implement the same feature with CC and Codex just to compare results, and I yet to find Codex making better decisions or even the completeness of the feature.

For more complicated stuff, like queries or data comparison, Codex seems always behind for me.

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maybe they decided OpenAI has different market, hence comparing only with companies who are focusing in dev tooling: Claude, GLM
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Haven’t you heard about Codex?
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its an SKU from OpenAI's perspective, broader goal and vision is (was) different. Look at the Claude and GLM, both were 95% committed to dev tooling: best coding models, coding harness, even their cowork is built on top of claude code
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I'm not sure how this makes sense when Claude models aren't even coding specific: Haiku, Sonnet, Opus are the exact same models you'd use for chat or (with the recent Mythos) bleeding edge research.
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Anthropic models and training data is optimized for coding use cases, this is the difference.

OpenAI on the other hand has different models optimized for coding, GPT-x-codex, Anthropic doesnt have this distinction

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But they detect it under the hood and apply a similar "variant", as API results are not the same than on Claude Code (that was documented before by someone).
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Yeah GLM’s great for coding, code review, and tool use. Not amazing at other domains.
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I use it and think its intelligence compares favorably with OpenAI and Anthropic workhorses. Its biggest weakness is its speed.
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