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

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

#261

Post by cmrdporcupine »

re-thc wrote: post #172
cmrdporcupine wrote: post #92

Earlier quoted context omitted.

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 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.

That's what I love about it, and I wish I could find an open model that was as diligent.

Somehow it's just way more careful than the others, and also much better at empirical verification of its hypothesis, writing tests, etc. I am assuming a lot of RL done on that kind of flow, and on seeking out negative cases, failure points, race conditions.

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

#262

Post by tw1984 »

marcus_cemes wrote: post #195
tcp_handshaker wrote: post #137

Earlier quoted context omitted.

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…

To be honest, living in Switzerland and speaking with peers, we're just exhausted by the constant AI hype. For a lot of us, the fact that Europe isn't frantically trying to scrape the entire internet and every book in existence for the next massive model isn't a bad thing. The big players are doing their thing, like with the nuclear arms race. We regulate a lot, too much a lot of the time, but sometimes that trickles…

[flagged]

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

#263

Post by program_whiz »

bitmasher9 wrote: post #121
CubsFan1060 wrote: post #107

Earlier quoted context omitted.

What kind of hardware/price does it take to run those?

Nvidia will sell you an entire server rack ready for inference. Or maybe you can roll out your own Blackwell based system. We’re approaching a world where running a primer frontier model is possible on a workstation, probably will have something under $30k that looks like a desktop for Nvidia’s next generation. It sounds expensive, until you look at your Anthropic bill. It’s similar unit economics as could computing…

"approaching" is doing some work there. $30K today will get you 90-144GB usable VRAM with solid system RAM and disk and CPU. A single B200 chip at 180GB is $40K. Unfortunately that is nowhere close to being able to run a 750B param model. For something like that, we're getting closer to 1TB VRAM (8+ H200/B200), and then 1M context KV cache is many more GBs on top of that.

That's a $500K-$1M+ rig as of now. That's a lot of $200 subscriptions to break even, but reasonable if you are paying Anthropic $25/M tokens. Then of course there's the power, cooling, and maintenance to consider...

But yeah, I can see if the prices come down 10x in a few years, or crater after the bubble, $30-40k might get you a decent machine.

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

#265

Post by gbingles »

robmccoll wrote: post #126
Tiberium wrote: 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…

That's interesting. I gave nearly the same task to Gemma4 31b as a test yesterday. Write a symbolic math engine in Typescript that can perform evaluation and simple expression reductions over +-/*(). It performed the task correctly with minimal reasoning - much fewer reasoning tokens than output tokens.

Tbh, so what? I googled "symbolic math engine in Typescript that can perform evaluation and simple expression reductions over +-/*()" and got what looks to be viable answers without using any AI model at all. Reciting well established things from memory isn't terribly interesting. Show it a novel codebase and have it implement something within it.

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

#267

Post by adastra22 »

saltsucker wrote: post #210
giancarlostoro wrote: post #155

Earlier quoted context omitted.

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

A year or so ago XML worked more reliably for long-lived prompt instructions. Now it is cargo culting.

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

#268

Post by vunderba »

kristopolous wrote: post #162
Certhas wrote: post #154

Earlier quoted context omitted.

None of these models come from universities, European or otherwise. Mistral is clearly currently not competing for Frontier Model. Whether this is due to a lack of VC Funds or a lack of technical ability or the former arising from the latter would be interesting to know. The top models are from startups. Among the FAANG only Google managed to get a Frontier model, and they litterally invented the architecture and hav…

I'm actually more curious about IBM. Their granite series appears to be nowhere close to competitive. They had Watson, remember, it won on jeopardy like 15 years ago? They've been at this for a long time Maybe it's good at something else?

I view Watson in the same light as Deep Blue, one-offs that brought more prestige and potential share value to IBM than necessarily "moving the needle" in the respective technology.

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

#269

Post by rapind »

JKCalhoun wrote: post #232
applicative wrote: post #206

Earlier quoted context omitted.

> China is going to eat the US lunch on AI They will forever have superior weights?

I would imagine it will be a fundamental breakthrough, not weights alone, that are going to usher in the next generation of AI. Perhaps China will in fact make that breakthrough. They certainly seem to have a lot of eyeballs in the field right now.

I think they are already massively winning on efficiency... which is about to matter a lot as the frontier models jack up their prices in order to some day see a profit (and no, Anthropic getting massively subsidized by Elon out of spite doesn't count for long term profits).

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

#270

Post by gbingles »

re-thc wrote: post #172
cmrdporcupine wrote: post #92

Earlier quoted context omitted.

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 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 AI review cycle can spiral infinitely figuratively debating what makes art good, and your code will be no better for it.

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