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GLM-5.2 is the new leading open weights model on Artificial Analysis

artificialanalysis.ai

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Re: GLM-5.2 is the new leading open weights model on Artificial Analysis

#141
post #2

It seems to really be a nice step-up and is getting quite close to the frontier. I wish they'd start focusing on the reasoning efficiency now, though. I have a simple (relatively) test task to evaluate LLMs: writing a simple math evaluator library in Nim (it's about 400-600 lines total max), and GLM 5.2 (xhigh which maps to max effort) spent over 15 minutes (!) reasoning, spending about 45k tokens, before it finally…

Hopefully the recent work Moonshot did with Kimi K2.7 Code trickles in to the other open-model labs.

Per AA, while K2.7 Code is roughly on par w/ K2.6 in terms of intelligence, it uses half the output tokens to get there.

Re: GLM-5.2 is the new leading open weights model on Artificial Analysis

#142
post #113

Earlier quoted context omitted.

Consider using decrementing score order (best on top)

then I'd have to scroll up over 500 lines after running it every time to see what I care about. But if that's your thing, here you go: https://github.com/day50-dev/aa-eval-email/commit/1853be6461... add an argument (any argument) and it will be sorted as your specified. It just works as a toggle flipping the order ... so literally any string will do. The original link has been updated accordingly with the new code.

Have it print paginated or just top 10?

Re: GLM-5.2 is the new leading open weights model on Artificial Analysis

#143
post #71

Artificial Analysis coding benchmark shows GLM5.1 on high pretty close to GPT5.5 xhigh in cost to run, with GPT5.5 on medium significantly less expensive. Compared to GPT5.5 medium GLM5.1xhigh is twice the cost and half the intelligence. They don't have GLM5.2 on there yet, but that'd a big gap to bridge. https://artificialanalysis.ai/agents/coding-agents?coding-ag... I thought I was "holding it wrong" until DeepSWE…

I gave GLM 5.2 a spin on openrouter yesterday and it was mostly fine but it racked up $5 in token use in 30 minutes of (relatively slow) work. It's easily 4x the cost of DeepSeek V4 but I didn't actually feel the results were that much better. I had GPT 5.5 in Codex review it after it was done and there was plenty of slop to go around. Having better luck with MiniMax M3, from a cost/benefit ratio.

I really like DeepSeek V4 Pro. It's pretty smart and I get so much usage out of it on a $20 Ollama cloud plan.

With a good harness, that's my favorite model for any personal project. I use Opus 4.8 at work because i don't have to pay for it and of course I love it, but DeepSeek is like 80% there for one tenth of the price.

Re: GLM-5.2 is the new leading open weights model on Artificial Analysis

#144
post #115

Earlier quoted context omitted.

Thanks for sharing. I'm curious: why didn't you sort with the score descending?

Because it's currently 511 lines. Why would I want to scroll up to see the stuff I care about? Don't you want the relevant stuff to be right there in front of you?

I do and that's why I pipe the output to `head -n 20` or use `LIMIT 20` in SQL.

That aside, this is a good script you're running. Thanks.

Re: GLM-5.2 is the new leading open weights model on Artificial Analysis

#145

Earlier quoted context omitted.

You're seriously suggesting that setting up opencode or tweaking your claude code config or etc is too much trouble to be worth saving $50 /mo? That's absurd. Doubly so when the audience in question is already using LLMs so ... just ask your existing LLM for help if it seems daunting.

I'm not just suggesting that, I'm trying to be crystal clear: it's a gap that probably cuts TAM by 95% or more. Most LLM users are not software engineers. Even those that are don't care enough to muck with their settings to try out a model. Keep in mind I'm not answering the question "Is this hard to install?" - I'm answering the question "Why aren't people talking about this?"

I would broadly agree with this (based on years of dealing directly with user-facing UX and setup steps). Small hurdles, even easy ones, create larger barriers to adoption then you’d think.

Re: GLM-5.2 is the new leading open weights model on Artificial Analysis

#146

I tried it today through Openrouter and the API is atrocious. I got multiple rate limit and random errors every turn. Somebody wrote [1]; "I am never touching Minimax or GLM again. Their APIs had constant outages and I had to restart my runs multiple times — after burning money on the runs that failed midway." and I 100% agree. The model might be good, but if the API is so bad, it's effectively useless. [1]: https://…

The entire point of this post is that it's open weights, you can run it yourself and don't have to deal with the API issues. You really do have that choice.

Re: GLM-5.2 is the new leading open weights model on Artificial Analysis

#147

Earlier quoted context omitted.

Isn't it closer to sonnet?

Definitely opus level for coding.

Do you have benchmarks or at least anecdotes to back that up? I'm not arguing with you; I would just love to see some proof that open models are getting as good as Anthropic's models.

Re: GLM-5.2 is the new leading open weights model on Artificial Analysis

#149
post #90

Earlier quoted context omitted.

Unless you have genuine national security concerns, you’d be better off just negotiating a commercial agreement with privacy protections with a couple of existing vendors.

if you can afford the investment you get stable low costs for years with better security (at least if your cyber team is good). its even better in regulated industries where some vendors might add a premium for hipaa/soc/pci dss compliance to the point its a lot cheaper to self host. for a smaller business its not worth it and you should just use a hosted open model.

> to the point its a lot cheaper to self host

I'm pretty skeptical, especially given typical utilization patterns. Do you have numbers, or this is just vibes?

Re: GLM-5.2 is the new leading open weights model on Artificial Analysis

#150

Earlier quoted context omitted.

score age size name 62.0 8 - Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) 59.1 55 - GPT-5.5 (xhigh) 58.5 55 - GPT-5.5 (high) 57.2 104 - GPT-5.4 (xhigh) 56.7 20 - Claude Opus 4.8 (Adaptive Reasoning, Max Effort) 56.2 55 - GPT-5.5 (medium) 55.5 118 - Gemini 3.1 Pro Preview 53.1 132 - GPT-5.3 Codex (xhigh) 53.1 62 - Claude Opus 4.7 (Non-reasoning, High Effort) 52.5 62 - Claude Opus 4.7 (Adaptive Re…

Short comments... - GPT 5.5 consistently the best, an opinion who gets me constant downvotes here by the Anthropic Marketeer strike force... - China is going to eat the US lunch on AI - What have European universities and companies been doing? Its like if, on a parallel past/future, Nikola Tesla and Edison would have created flying Cyberpunk machines, while Europeans researchers, would be getting together to request…

They did muse spark ... it's not garbage.

Also what are they building it for? I'd think it's to serve ads better or something like that. Maybe Muse Spark fits facebook's needs perfectly...

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