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

artificialanalysis.ai

201–210 of 476 posts

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

#201

I've been playing with this model a fair amount over the last 24 hours, and I can confirm it's quite capable, while being a little bit verbose (I've seen it reconsider things 3-4 times in thinking traces before deciding on a path forward), and not being quite as good as GPT5.5 at working through complex abstract requirements. Honestly it's good enough that I feel comfortable recommending a Z.AI sub + a $20/mo OpenAI…

> GLM writing

This is honestly what I care bout the most now, which is how well they can write. I think we have reached a point now, if you know how to program, you can provide enough information for the models to pretty much do what you need.

What they still struggle immensely with is the writing which has too many nuances but they are truly getting better.

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

#202

Earlier quoted context omitted.

GLM 5.2 Max = Opus 4.8 Max in thinking behavior. The thinking chain is so similar, and so is the amount of token usage on the output. If you want reasonable token usage, you need to run it GLM 5.2 at High. There is little drop in quality from Max to High (for most tasks). And it cuts token usage by 2 a 2.5x. GLM 5.2, Max is really something you only need for complex tasks. In essence, GLM 5.2 is Opus 4.8 its little b…

distillation of thinking models is not particularly effective - both "Open"AI and Misanthropic don't show you the real chain of thought, only its severely downscaled version. both do everything in their power to combat such outrageous copyright infringement, so the bulk of unethically scrapped data the Chinese have is from several generations ago.

The companies that did copyright infringement and unethically scrapped data think that copyright infringement and unethically scrapping data is wrong and needs to be stopped.

Though only in particular situations, like when it’s done to them and not when they do it. Cause they have the power and are morally right and know better than you. And if you question this at all, well you’re a threat to American values and a supporter of the Chinese and leading to the break down of Democracy.

This isn’t a type of reasoning argument or manipulation tactic used by the rich throughout history to trick the naive and gullible masses or anything like that. Trust me, I’m rich and I’m morally right. /sarcasm

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

#203
post #110

I was surprised that GLM 5.1/5.2 are not vision models - they are text input only. That's actually pretty uncommon these days. All of the OpenAI/Anthropic/Gemini models accept images, and so do the other leading open weight families - Gemma 4, Qwen 3.6, Kimi 2.x. In GLM's case image input would be useful because it's a model that scores very highly for tasks like web design, but without image input it can't take a sc…

Configure a subagent in your coding harness to spin up a new sub-session with any vision model for those tasks and feed the result back to the main model. No need for "one model that does everything"

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

#204

DeepSeek v4 pro is still 10x cheaper than GLM-5.2 and the quality is still enough for 95% of coding tasks.

People always say stuff like this, but it is misleading. The reason it's misleading is because that remaining 5% makes a huge difference, and is where most of the value of using AI agents lies.

I'm not interested in using AI to write code that would have taken me 5-10 minutes to write myself. I use AI to debug complex bugs and develop large features that span multiple domains - stuff that normally takes hours, if not days/weeks. A model that is "enough for 95%" does not cut it for that, because the failures compound during long-horizon tasks and the thing becomes a mess.

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

#205

Just ran and scored 63 3d model generations (via code) across high and no reasoning. 3D Modeling benchmark quickly shows spatial, logic and code performance of the model so I think it's a very good indicator of the quality. Here are the results compared to Gemini 3.5 Flash: Model + config CodeErr/gen Cost/gen Median time Quality gemini-3.5-flash, low 0.71 $0.18 68s baseline GLM 5.2, reasoning high 0.61 $0.18 289s -6.…

Very interested in this! Can you share more about the modelling method (eg, three js?), the task list, and outputs here?

I think there's probably some good juice to squeeze in terms of spacial awareness by doing a benchmark something like

- give 3d modelling task

- render and snapshot from a variety of angles

- feed to third-party vision model for a "what is this" type query

- grade on end-to-end accuracy

Bonus points for asking the vision model something like "how beautiful is this 1-10".

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

#206

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…

> China is going to eat the US lunch on AI

They will forever have superior weights?

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

#207

Sure, but whatever you do, don't buy their (Z.ai) lite plan. I feel like i threw 15 dollars in the sea. I'm getting rate limited after 3-4 prompts. You get way less value than just paying 25 dollars for Claude or OpenAI models.

Did you consider their peak hours and model usage multiplier? Read the green box https://docs.z.ai/devpack/overview#usage-instruction

I had the Lite plan, I NEVER maxed out the quota because I considered these things. If I, for example, switched over to GLM-5-Turbo, then I could've easily burned through quota.

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

#208

DeepSeek v4 pro is still 10x cheaper than GLM-5.2 and the quality is still enough for 95% of coding tasks.

....so use DeepSeek v4 Pro for 95% of your coding tasks, and GLM 5.2 for the other 5%? You don't need to stick to one model.

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

#209
post #24

Correct me if I'm wrong, but neither DeepSeek nor GLM have image input modality. This makes them less useful when looking at UIs, photos, screenshots, etc. doesn't it? Or do they have alternate ways of doing so?

Configure a subagent in your coding harness for vision, add a prompt about the vision use, configure a vision model for it, modify your main agent's prompt to use the vision subagent for vision tasks. Now your non-vision model has vision support.

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

#210
post #140

Earlier quoted context omitted.

XML??

Apparently because of how Claude is trained, even the system level prompts go through as XML, it works better with XML "prompting" so I figured I could have it write plans in XML. I need to update my ticketing tool to output XML maybe by default. https://www.reddit.com/r/ClaudeAI/comments/1psxuv7/anthropic...

Comments later in thread say markdown works just as fine and that it’s more important to organize your plan into sections.

Also just think about it, why would a model trained on the world’s corpus of text (that isnt formatted in xml) perform better with XML? It would be a better study if that post tested markdown, org, xml, json, etc. 10 times to see if their is a difference

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