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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

#291

Post by swingboy »

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

Anthropic’s best practices still include the use of XML: https://platform.claude.com/docs/en/build-with-claude/prompt...

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

#292

Post by overfeed »

happyPersonR wrote: post #217
RyanHamilton wrote: post #96

Earlier quoted context omitted.

Could it be possible, these firms are optimizing for two things: a) Better performance. b) Gathering data from you to further improve performance later. I've also found the huge amount of planning rather than iteration frustrating. I've felt like I'm teaching a junior!

more thinking == more tokens === more money LOLL

Os there a cost benchmark out there? I wonder how frontier models are doing over time for cost per problem solved.

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

#294

Post by NiloCK »

ponyous wrote: post #243
NiloCK wrote: post #205

Earlier quoted context omitted.

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 point…

I don't have the eval results live yet, so I cannot share them yet. I was benchmarking using a soon to be released new version of my AI CAD modeling software[0]. It's basically an agent that has access to tools that can execute build123d scripts, get sculpted models, blender to combine sculpts + parametric models, tools to inspect the model (visually and with code), search datasheets, ... I tried what you recommend a…

Very cool project. Thanks for sharing!

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

#295

Post by spelk »

zooming wrote: post #106
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.

Try MiMo-2.5, I'm having astonishing success with it in opencode for cents per day. Not even the pro model.

I've found MiMo-2.5 is fun for front-end design since you can use its multimodal capabilities to drop in whatever it produced and correct it for you.

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

#296

Post by stymaar »

simianwords wrote: post #200
stymaar wrote: post #119

Earlier quoted context omitted.

> No models are subsidised We have no proof in either direction, it's not like we had access to their financial numbers in details. And the pricing itself muddies the water, as input tokens that are already in the KV cache are practically free for the provider, whereas other tokens are expensive. So they could still make money overall thanks to people having multi-turn conversation (and as such, paying multiple times…

> How can you be sure You are free to believe that they are doing all this. Or you can simply believe the intuition that models are getting cheaper by the day. I can run Gemma 4 31B from my laptop today.

> Or you can simply believe the intuition

Sure, you can believe you intuition as much as you want, but telling strangers over the internet that they are wrong because “I trust my intuition” is… awkward.

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

#297

Post by spelk »

benjiro29 wrote: post #65
stanac wrote: post #26

Earlier 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/$0.08/$…

Neuralwatt ... When you reverse calculate the actual energy usage / price on a token basis, the gap is large. I do not have GLM 5.2 numbers because the whole default max setting is overkill. But GLM 5.1 numbers had it at 12x cheaper then API rates. And about 2.5x more tokens vs zai their own subscription service. Yes, its FP8 but lets be honest, do we know for sure that even zai runs at FP16? I learned a long time ag…

Please correct me if you have contradicting data but: Neuralwatt's price per token vs price for energy comparison doesn't seem to take into account the cost savings from cache hits that other providers offer on pure token rates. The comparison seems to assume every input token is a cache miss.

On top of that, the cloud offering doesn't seem that well-run, they randomly blocked a colleague's API key for a couple days without any heads up, had a weird rate limiting bug and they have been deprecating models without redirects with very short notice, all while taking weeks to onboard new models. I assume some of these problems would be addressed if we had an SLA/enterprise contract.

It's a promising idea though. They offer a $5 trial credit (with an aggressive rate limit) though so no harm in trying it out.

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

#298

Post by OKRainbowKid »

tw1984 wrote: post #262
marcus_cemes wrote: post #195

Earlier quoted context omitted.

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]

You seem to be confusing Hacker News with 4chan.

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

#299

Post by spelk »

unrvl22 wrote: post #6
unrvl22 wrote: post #4

Why aren't more people talking about this? It's literally Opus 4.7 quality stupid prices. I know providers who are offering this at unlimited tokens for $50 a month. Some are even offering API rates at 3x lower than the official ZAI api rates which are already like 10x cheaper than Opus. (Crof and Umans btw) This is a huge blow to Anthropic/OpenAI/Google and a massive win for the rest of the world. The official API p…

I cancelled my claude sub after realizing I can burn 300m tokens a day of this quality, for $50 a month.

Which coding plan are you using? How are you finding it?

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

#300

Post by drob518 »

vorticalbox wrote: post #29
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…

This is a problem I find with opus is will spend so long thinking then going “but wait what if” To point where I stop it and simple tell it to “start writing code you can work it out as you go along” Seems writers block also effects LLM

Qwen is notorious for this, too. It’ll sometimes spin in a long loop of “But wait…” paragraphs.
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