Hmmm... GLM insists it's Gemini. https://github.com/zai-org/GLM-5/issues/79
Then why does it score better than any Gemini model?
GLM-5.2 is the new leading open weights model on Artificial Analysis
271–280 of 476 posts
Re: GLM-5.2 is the new leading open weights model on Artificial Analysis
#272Earlier 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.
FYI: model outputs are not protected by copyright.
Re: GLM-5.2 is the new leading open weights model on Artificial Analysis
#273I have a script that ranks these based on codingindex from Artificial Analysis. All it does is pull a json from their main table page and parses it with the fields I care about (coding). There used to be a mailing list associated with it but eh ... there wasn't much interest. I use the script every day though. Current partial output score age size name 47.1 58 large Kimi K2.6 47.5 54 large DeepSeek V4 Pro (Reasoning,…
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…
rank score age size name
1 62.0 8 - Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback)
2 59.1 55 - GPT-5.5 (xhigh)
3 58.5 55 - GPT-5.5 (high)
4 57.2 104 - GPT-5.4 (xhigh)
5 56.7 20 - Claude Opus 4.8 (Adaptive Reasoning, Max Effort)
6 55.5 118 - Gemini 3.1 Pro Preview
7 53.1 62 - Claude Opus 4.7 (Non-reasoning, High Effort)
8 53.1 132 - GPT-5.3 Codex (xhigh)
9 52.5 62 - Claude Opus 4.7 (Adaptive Reasoning, Max Effort)
10 51.5 92 - GPT-5.4 mini (xhigh)
11 50.9 120 - Claude Sonnet 4.6 (Adaptive Reasoning, Max Effort)
12 50.7 1 large GLM-5.2 (max)
13 50.1 29 - Qwen3.7 Max
14 48.7 188 - GPT-5.2 (xhigh)
15 48.1 132 - Claude Opus 4.6 (Adaptive Reasoning, Max Effort)
16 47.8 205 - Claude Opus 4.5 (Reasoning)
17 47.6 132 - Claude Opus 4.6 (Non-reasoning, High Effort)
18 47.5 70 - Muse Spark
19 47.5 54 large DeepSeek V4 Pro (Reasoning, Max Effort)
20 47.1 58 large Kimi K2.6
21 47.1 29 - Gemini 3.5 Flash (minimal)
22 46.7 449 - Gemini 2.5 Pro Preview (Mar' 25)
23 46.5 211 - Gemini 3 Pro Preview (high)
24 46.5 16 - Qwen3.7 Plus
25 46.4 120 - Claude Sonnet 4.6 (Non-reasoning, High Effort)
26 45.6 5 large Kimi K2.7 Code
27 45.6 104 - GPT-5.4 (low)
28 45.5 56 large MiMo-V2.5-Pro
29 45.1 43 - GPT-5.5 Instant (May 2026)
30 45.0 29 - Gemini 3.5 Flash (high)
31 44.9 58 - Qwen3.6 Max Preview
32 44.7 216 - GPT-5.1 (high)
33 44.2 188 - GPT-5.2 (medium)
34 44.2 126 large GLM-5 (Reasoning)
35 43.9 92 - GPT-5.4 nano (xhigh)
36 43.4 71 large GLM-5.1 (Reasoning)
37 43.4 16 large MiniMax-M3
38 43.2 54 large DeepSeek V4 Pro (Reasoning, High Effort)
39 43.0 188 - GPT-5.2 Codex (xhigh)
40 42.9 76 - Qwen3.6 Plus
41 42.9 205 - Claude Opus 4.5 (Non-reasoning)
42 42.6 182 - Gemini 3 Flash Preview (Reasoning)
43 42.2 99 - Grok 4.20 0309 (Reasoning)
44 42.1 56 large MiMo-V2.5
45 41.9 91 large MiniMax-M2.7
46 41.4 91 - MiMo-V2-Pro
47 41.3 121 large Qwen3.5 397B A17B (Reasoning)
48 41.0 48 - Grok 4.3 (high)
49 40.5 71 - Grok 4.20 0309 v2 (Reasoning)
50 40.5 342 - Grok 4
51 39.8 54 large DeepSeek V4 Flash (Reasoning, High Effort)
Re: GLM-5.2 is the new leading open weights model on Artificial Analysis
#274Earlier quoted context omitted.
> I had GPT 5.5 in Codex review it after it was done and there was plenty of slop to go around. GPT can find fault in everything and anything including its own work.
AI review generally will find fault in anything. Any non-trivial code has multiple solutions with different tradeoffs. Any code can be over-engineered for theoretical edge cases and future use cases you don't need. No matter which solution you pick you can always at a minimum say that some alternative just looks and reads better. Code is somewhat artistic. If you don't have well defined standards and priorities, the…
This is correct, but I'd say there's something beyond that that's more specific about Codex + GPT models though. They've done some sort of training that makes it far more diligent about seeking out data races, unhandled errors / negative cases, and missing test coverage than the other models I've played with. It also seems more prone to testing its hypothesis.
This makes it slower to work with for prototyping, and it will, if not properly disciplined, litter your code with "legacy adapters" and "bridge code" and temporary incremental refactoring steps [arguably not terrible for work in real commercial software projects]. And it will create too many unit & integration tests, if you're not careful.
But it does, in my opinion, tend to produce more reliable software and I trust it far more than I did when I was working in Claude.
When I could afford it, I had both plans running, Claude to produce new features, and then Codex to brutally critique it battle test it, sharpen the edges, and produce better tests, and this flow went extremely well.
Now I just work with Codex and various open models.
Re: GLM-5.2 is the new leading open weights model on Artificial Analysis
#275Re: GLM-5.2 is the new leading open weights model on Artificial Analysis
#276According to many benchmarks this model is straight up frontier level and Zai seriously cooked. Some of these numbers are incredible. Excited to see if this turns out to be a Open Weight Opus 4.5 or better.
According to reports in this thread it is somewhere between Opus 4.7 and 4.8. This is effectively frontier.
Re: GLM-5.2 is the new leading open weights model on Artificial Analysis
#277Earlier quoted context omitted.
> Some are even offering API rates at 3x lower than the official ZAI api rates Looking at openrouter [1], some of the cheaper offerings are for quantized models. Not sure how much intelligence is lost in quantization. And they are not 3 times cheaper. Where did you find 3x lower prices for APIs? I am considering skipping open router and using them directly for that price. edit: I see, croft [2] 8bit for $0.50/$0.08/$…
IME, unquantised -> FP8 is pretty much lossless. What matters more is having an unquantized KV cache - using an FP8 KV cache can result in a significant drop in quality.
>unquantised -> FP8 is pretty much lossless
Claude Shannon is rolling in his grave.
Re: GLM-5.2 is the new leading open weights model on Artificial Analysis
#278Earlier 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…
I also get the downvotes for the GPT thing, and agree with you about 5.5's quality, but TBH I don't think it's Anthropic marketing as just two other things:
1. SamA and his company has a well-deserved bad reputation and Anthropic got some early good PR for basically not being SamA.
2. Claude Code got early head space, Boris and crew basically "invented" this kind of agent, and so has first mover advantage despite its known reliability and cost issues.
3. Most people I talk to haven't even tried Codex for some reason
Also it's uncool to complain about downvotes.
Re: GLM-5.2 is the new leading open weights model on Artificial Analysis
#279Earlier quoted context omitted.
To answer the question in your first sentence - because it's VERY computationally (ha) expensive as a human being to keep up with all the options. It's also very hard to figure out how to run a model like this. There's no installer . If you really really care, which 99% of people do not, you have to google a guide, and then find out it's out of date... I've tried a number of these, and the learning curve is very stee…
> There's no installer. There's ZCode ( https://zcode.z.ai ). Which is like the Codex App. That's as "easy" as it is for non-devs that you're complaining about.
How does it compare to OpenCode? I already have too many LLM CLIs installed :(
Re: GLM-5.2 is the new leading open weights model on Artificial Analysis
#280Earlier quoted context omitted.
Sure, I'm not saying I, a software engineer, cannot do this. I'm saying it's significant onboarding friction . Unless this were a massive differentiator, people aren't going to be "talking about it" the way GP suggests!
> it's significant onboarding friction. It's crazy that apparently writing software without knowing how to edit a single config file is normal now.
It's crazy that apparently doing math without knowing how to do long division by hand is normal now.