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GLM-5: Targeting complex systems engineering and long-horizon agentic tasks
- ExpertAdvisor01 8mo agoThey increased their prices substantially
- cl0ckt0wer 9mo agoSoft launch? I can't find a blog post on their website.
- cl0ckt0wer 9mo agoThe second sentence from a creative writing prompt: Valerius stood four meters tall—roughly thirteen feet. He was not merely a Space Marine; he was a biological singularity. I'm surprised they still have the emdash and "not x, but y" quirks
- htrp 9mo agodistillation is a hell of a drug
- mythz 9mo agoThey announced it on twitter [1]: > A new model is now available on http://chat.z.ai http://chat.z.ai. Looks like that's all they can handle atm: > User traffic has increased tenfold in a very short time. We’re currently scaling to handle the load. [1] https://x.com/Zai_org/status/2021564343029203032 https://x.com/Zai_org/status/2021564343029203032
- zozbot234 9mo agoThere was a one-line X post about something new being available at their chat endpoint, but that's about it at the time of this writing. Nothing at GitHub or HuggingFace, no tech report or anything.
- linolevan 9mo agoWhat's funny is it's available on /v1/models, but if you call it you get an error saying it's not accessible yet. No word on pricing, probably the same as 4.7 if I had to guess (0.6/2.2)
- deleted 9mo ago[deleted]
- Mashimo 9mo agoWut? Was glm 4.7 not just a few weeks ago? I wonder if I will be able to use it with my coding plan. Paid just 9 usd for 3 month.
- ExpertAdvisor01 9mo agoNope. Lite plan receives only same-tier model updates.
- Havoc 9mo agoI don't see it as selectable my side either (opencode & max plan)
- ExpertAdvisor01 9mo agoThey updated it now
- Havoc 8mo agoNo luck here. Did you do anything specific to make it show / reauth or something? ah nvm - found the guidance on how to change it
- _joel 9mo agoIt's avaiable in mine, I think I paid about the same
- NitpickLawyer 9mo ago> It's avaiable in mine Weird, mine (lite plan) says "Only supports GLM-4.7, GLM-4.6, GLM-4.5, and GLM-4.5-Air" and "Get same-tier model updates" ...
- Mashimo 9mo agoIt seems like nothing is updated yet, expect the chat. https://z.ai/subscribe https://z.ai/subscribe It all just mentions 4.7 Seems like time will tell. Edit: They updated it: > The Lite / Pro plan currently does not include GLM-5 quota (we will gradually expand the scope and strive to enable more users to experience and use GLM-5). If you call GLM-5 under the plan endpoints, an error will be returned. If you still wish to experience GLM-5 at this stage and are willing to pay according to the Pricing, you can call it through the General API endpoint (i.e., https://api.z.ai/api/paas/v4/chat/completions https://api.z.ai/api/paas/v4/chat/completions), with the deduction priority being [Platform Credits - Account Balance] in sequence.
- mythz 9mo agoIt's looking like we'll have Chinese OSS to thank for being able to host our own intelligence, free from the whims of proprietary megacorps. I know it doesn't make financial sense to self-host given how cheap OSS inference APIs are now, but it's comforting not being beholden to anyone or requiring a persistent internet connection for on-premise intelligence. Didn't expect to go back to macOS but they're basically the only feasible consumer option for running large models locally.
- mikrl 9mo ago>I know it doesn't make financial sense to self-host given how cheap OSS inference APIs are now You can calculate the exact cost of home inference, given you know your hardware and can measure electrical consumption and compare it to your bill. I have no idea what cloud inference in aggregate actually costs, whether it’s profitable or a VC infused loss leader that will spike in price later. That’s why I’m using cloud inference now to build out my local stack.
- mythz 9mo agoNot concerned with electricity cost - I have solar + battery with excess supply where most goes back to the grid for $0 compensation (AU special). But I did the napkin math on M3 Ultra ROI when DeepSeek V3 launched: at $0.70/2M tokens and 30 tps, a $10K M3 Ultra would take ~30 years of non-stop inference to break even - without even factoring in electricity. You clearly don't self-host to save money. You do it to own your intelligence, keep your privacy, and not be reliant on a persistent internet connection.
- NiloCK 9mo ago> Didn't expect to go back to macOS but their basically the only feasible consumer option for running large models locally. I presume here you are referring to running on the device in your lap. How about a headless linux inference box in the closet / basement? Return of the home network!
- Aurornis 9mo ago
- tosh 9mo agoafaiu this will also be an open weight release (soon?)
- tosh 9mo agoapparently the 'pony-alpha' model on OpenRouter was GLM-5 https://openrouter.ai/openrouter/pony-alpha https://openrouter.ai/openrouter/pony-alpha z.ai tweet: https://x.com/ZixuanLi_/status/2020533168520954332 https://x.com/ZixuanLi_/status/2020533168520954332
- seaal 9mo agoPeople that were tracking this were already aware but glad to have confirmation. This blog post I was reading yesterday had some good knowledge compilation about the model. https://blog.devgenius.io/z-ais-glm-5-leaked-through-github-prs-and-a-zodiac-easter-egg-8716deb07f93 https://blog.devgenius.io/z-ais-glm-5-leaked-through-github-...
- guld 9mo agoLet's hope they release it to huggingface soon. I tried their keyboard switch demo prompt and adapted it to create a 2D Webgl-less version to use CSS, SVG and it seem to work nicely, it thinks for a very long time however. https://chat.z.ai/c/ff035b96-5093-4408-9231-d5ef8dab7261 https://chat.z.ai/c/ff035b96-5093-4408-9231-d5ef8dab7261 [1] https://huggingface.co/zai-org https://huggingface.co/zai-org
- cmrdporcupine 9mo agoBought some API credits and ran it through opencode (model was "GLM 5"). Pretty impressed, it did good work. Good reasoning skills and tool use. Even in "unfamiliar" programming languages: I had it connect to my running MOO and refactor and rewrite some MOO (dynamic typed OO scripting language) verbs by MCP. It made basically no mistakes with the programming language despite it being my own bespoke language & runtime with syntactical and runtime additions of my own (lambdas, new types, for comprehensions, etc). It reasoned everything through by looking at the API surface and example code. No serious mistakes and tested its work and fixed as it went. Its initial analysis phase found leftover/sloppy work that Codex/GPT 5.3 left behind in a session yesterday. Cost me $1.50 USD in token credits to do it, but z.AI offers a coding plan which is absolutely worth it if this is the caliber of model they're offering. I could absolutely see combining the z.AI coding plan with a $20 Codex plan such that you switch back and forth between GPT 5.3 and GLM 5 depending on task complexity or intricacy. GPT 5.3 would only be necessary for really nitty gritty analysis. And since you can use both in opencode, you could start a session by establishing context and analysis in Codex and then having GLM do the grunt work. Thanks z.AI!
- jfaat 9mo agoYeah that's a good idea. I played around with kimi2.5/gemini in a similar way and it's solid for the price. It would be pretty easy to build some skills out and delegate heavy lifting to better models without managing it yourself I think. This has all been driven by anthropic's shenanigans (I cancelled my max sub after almost a year both because of the opencode thing and them consistently nerfing everything for weeks to keep up the arms race.)
- cmrdporcupine 9mo agoYeah I did the same (cancel Anthropic). Mainly because the buggy/bloatiness of their tooling pissed me off and I got annoyed by Dario's public pronouncements (not that SamA is any better). I ended up impressed enough w/ GPT 5.3 that I did the $200 for this month, but only because I can probably write-off as business expense in next year's accounting. Next month I'll probably do what I just said: $20 each to OpenAI and Google for GPT 5.3 and Gemini 3 [only because it gets me drive and photo storage], buy the z.AI plan, and only use GPT for nitty gritty analysis heavy work and review and GLM for everything else.
- tgtweak 9mo ago5.0 flash with native sub-agents released to huggingface.... one can wish right :)
- NiloCK 9mo agoGrey market fast-follow via distillation seems like an inevitable feature of the near to medium future. I've previously doubted that the N-1 or N-2 open weight models will ever be attractive to end users, especially power users. But it now seems that user preferences will be yet another saturated benchmark, that even the N-2 models will fully satisfy. Heck, even my own preferences may be getting saturated already. Opus 4.5 was a very legible jump from 4.1. But 4.6? Apparently better, but it hasn't changed my workflows or the types of problems / questions I put to it. It's poetic - the greatest theft in human history followed by the greatest comeuppance. No end-user on planet earth will suffer a single qualm at the notion that their bargain-basement Chinese AI provider 'stole' from American big tech.
- miohtama 9mo agoIn some ways, Opus 4.6 is a step backwards due to massively higher token consumption.
- nwienert 9mo agoFor me, it's just plain worse.
- cmrdporcupine 9mo agoTry Codex / GPT 5.3 instead. Basically superior in all respects, and the codex CLI uses 1/10 the memory and doesn't have stupid bugs. And I can use my subscription in opencode, too. Anthropic has blown their lead in coding.
- toraway 9mo agoYeah, I have been loving GPT 5.2/3 once I figured out how to change to High reasoning in OpenCode. It has been crushing every request that would have gone to Opus at a fraction of the cost considering the massively increased quota of the cheap Codex plan with official OpenCode support. I just roll my eyes now whenever I see HN comments defending Anthropic and suggesting OpenCode users are being petulant TOS-violating children asking for the moon. Like, why would I be voluntarily subjected to worse, more expensive and locked down plan from Anthropic that has become more enshittified every month since I originally subscribed given Codex exists and is just as good? It won't last forever I'm sure but for now Codex is ridiculously good value without OpenAI crudely trying to enforce vendor lock-in. I hate so much about this absurd AI/VC era in tech but aggressive competition is still a big bright spot.
- mythz 9mo agoLets not miss that MiniMax M2.5 [1] is also available today in their Chat UI [2]. I've got subs for both and whilst GLM is better at coding, I end up using MiniMax a lot more as my general purpose fast workhorse thanks to its speed and excellent tool calling support. [1] https://news.ycombinator.com/item?id=46974878 https://news.ycombinator.com/item?id=46974878 [2] https://agent.minimax.io https://agent.minimax.io
- andai 8mo agoMy perspective aligns with this: I used to obsess over the Best Model, which I defined as "top of benchmarks", which also meant Biggest, Slowest and Most Expensive. Then I gave two models a Real World Task. The "Best" model took 3x longer to complete it, and cost 10x more. [0] Now I define Best Model as "the smallest, fastest, cheapest one that can get the job done". (Currently happy with GLM-4.7 on Cerebras, at least I would be if the unlimited plan wasn't sold out ;) I later expanded this principle when model speed crossed into the Interactive domain. Speed is not merely a feature; a sufficient difference in speed actually produces a completely new category of usage. [0] We recently arrived at an approximation of AGI which is "put a lossy solver in an until-done loop". For most tasks we're throwing stuff at a wall to see what sticks, and the smaller models throw faster.
- lab14 9mo ago- meh, i asked what happened to Virginia Guiffre and it told me that she's alive and well living with her husband and children in australia - i pointed out that she died on 2025 and then it told me that my question was a prank with a gaslighting tone because that date is 11 months into the future - it never tried to search the internet for updated knowledge even though the toggle was ON. - all other AI competitors get this right
- flaviolivolsi 9mo agoThat's not really an issue exclusive to GLM. Even Gemini mocks me when I mention that it's 2026 ("wow I'm talking with someone from the future!")
- mattkevan 9mo agoSonnet told me I was lying when I said that gpt-5 was a model that actually existed. It kept changing the code back to 4o and flatly refused to accept its existence.
- evrenesat 9mo agowhen I say "base your answers on search results", it did quite well: https://chat.z.ai/s/b44be6a3-1c72-46cb-a5f0-8c27fb4fdf2e https://chat.z.ai/s/b44be6a3-1c72-46cb-a5f0-8c27fb4fdf2e
- junon 9mo agoCan't search the web, asked about a project available on GitHub before its knowledge cutoff, and WOW it hallucinated\b\b bullshitted the most elaborately incorrect answer imaginable. Immediately deemed irrelevant to me, personally.
- DeathArrow 9mo agoI hope Cerebras offers this soon. Working with GLM-4.7 from Cerebras was a major boost compared with other models.
- maipen 9mo agoI loved the speed, but the cost is insane. A cerebras subscription would be awesome!
- kleiba 9mo agoHow do you get a domain like z.ai?
- Invictus0 9mo agoExpensively
- drcongo 9mo agoI asked chat.z.ai with GLM 5 "How do I start coding with z.ai?" and got this in the answer... > Z.ai (Personalized Video) If you literally meant the website z.ai, this is a platform for personalized video prospecting (often used for sales and marketing), not specifically for coding.
- CodeCompost 9mo ago[flagged]
- jdxcode 9mo agowasn't it 1989 technically?
- CodeCompost 9mo agoOh yeah, sorry.
- throwaw12 9mo agoAs I promised earlier: https://news.ycombinator.com/item?id=46781777 https://news.ycombinator.com/item?id=46781777 "I will save this for the future, when people complain about Chinese open models and tell me: But this Chinese LLM doesn't respond to question about Tianmen square." Please stop using Tianmen question as an example to evaluate the company or their models: https://news.ycombinator.com/item?id=46779809 https://news.ycombinator.com/item?id=46779809
- roywiggins 9mo agoThat's just whataboutism. Why shouldn't people talk about the various ideological stances embedded in different LLMs?
- throwaw12 9mo agoWhy do we hear censorship concerns only when it comes Chinese models? Why don't we hear similar stances when Claude or OpenAI releases models? We either set the bar and judge both, or don't complain about censorship
- roywiggins 9mo agoI think more people should spend time talking about this with American models, yeah. If you're interested in that then maybe that can be you. It doesn't have to be the same exact people talking about everything, that's the nice thing about forums. Find your own topic that American models consistently lie or freeze on that Chinese models don't and post about it.
- Mashimo 9mo agoDo we know if it as vision? That is lacking from 4.7, you need to use an mcp for it.
- Amol-917 9mo ago[flagged]
- Mashimo 9mo agoLooking at the other comments from this account, this seems like a bot
- Dowwie 9mo agoGLM5 is showing very disappointing general problem solving abilities
- LorenDB 9mo agoI occasionally see z.ai mentioned and then I remember that I had to block their email since they spammed me with an unsolicited ad. Since then I'm very skeptical of using them.
- eugene3306 9mo agowhy don't they publish at ARC-AGI ? too expensive?
- Bolwin 9mo agoArc agi was never a good benchmark that tested spatial understanding more than reasoning. I'm glad it's no longer popular
- falcor84 9mo agoWhat do you mean? It definitely tests reasoning as well, and if anything, I expect spatial and embodied reasoning to become more important in the coming years, as AI agents will be expected to take on more real world tasks.
- eugene3306 8mo agospatial or not, arc-agi is the only test that correlates to my impression with my coding requests
- beAroundHere 9mo agoI'd say that they're super confident about the GLM-5 release, since they're directly comparing it with Opus 4.5 and don't mention Sonnet 4.5 at all. I am still waiting if they'd launch GLM-5 Air series,which would run on consumer hardware.
- esafak 9mo agoI place GLM 4.7 behind Sonnet.
- revolvingthrow 9mo agoQwen and GLM both promise the stars in the sky every single release and the results are always firmly in the "whatever" range
- CuriouslyC 8mo agoQwen famously benchmaxxes. GLM is more robust, I'd say it's comparable to DeepSeek in that regard.
- esafak 9mo agoI got fed up with GLM-4.7 after using it for a few weeks; it was slow through z.ai and not as good as the benchmarks lead me to believe (esp. with regards to instruction following) but I'm willing to give it another try.
- valvar 8mo agoTry Cerberas
- odie5533 8mo agoI spent $10 in 2 minutes with that and gave up
- KronisLV 8mo agoTheir 50 USD per month plan gives you 24M tokens per day: https://www.cerebras.ai/pricing https://www.cerebras.ai/pricing
- wild_egg 8mo agoI had that for a few months and cancelled. They have minutely rate limits as well so you get 3-4 hyperspeed responses and then a 45 second pause waiting for the throttling to let your next request through. And then, depending on what you're working on, the 24M daily allotment is gone in under an hour. I regularly burned it in about 25 minutes of agent use. I imagine if I had infinite budget to pay regular API rates on a high usage tier, it would be really quite good though.
- KronisLV 8mo ago> They have minutely rate limits as well so you get 3-4 hyperspeed responses and then a 45 second pause waiting for the throttling to let your next request through. I haven’t really gotten that, though have noticed on some occasions: A) high server load notifications, most commonly, can delay an answer by about 3-10 seconds B) hangs, this happens quite rarely, not sure if a network issue or something on their side, but sometimes the submitted message just freezes (e.g. nothing happening in OpenCode), doesn’t seem deliberate because resubmitting immediately works, more often than not > And then, depending on what you're working on, the 24M daily allotment is gone in under an hour. I regularly burned it in about 25 minutes of agent use. That’s a lot of tokens, almost a million a minute! Since the context is about 128k, you’d be doing about 8 full context requests every minute for 25 minutes straight. I can see something like that, but at that point it feels like the only thing that’d actually be helpful would be caching support on their end. You must be on some pretty high tier subscriptions with the other providers to get the same performance!
- woah 9mo agoIs this a lot cheaper to run (on their service or rented GPUs) than Claude or ChatGPT?
- esafak 9mo agoYes. https://z.ai/subscribe https://z.ai/subscribe
- leumon 8mo agoalthough apparently only the max subscription includes glm-5
- muyuu 8mo agothey just removed the 50% discount today i can imagine they're a bit tight to keep those prices viable while they also have enough compute to train their new models
- Alifatisk 8mo agoI don’t think it is about viability. The Christmas discount was supposed to expire jan 15, then it was further expanded to jan 31. The deal was too good to miss out on.
- su-m4tt 9mo agodramatically cheaper.
- eunos 9mo agoRumour says that this model is exclusively trained on Huawei chips.
- algorithm314 9mo agoHere is the pricing per M tokens. https://docs.z.ai/guides/overview/pricing https://docs.z.ai/guides/overview/pricing Why is GLM 5 more expensive than GLM 4.7 even when using sparse attention? There is also a GLM 5-code model.
- logicprog 9mo agoI think it's likely more expensive because they have more activated parameters, which kind of outweighs the benefits of DSA?
- l5870uoo9y 8mo agoIt's roughly three times cheaper than GPT-5.2-codex, which in turn reflects the difference in energy cost between US and China.
- re-thc 8mo agoIt reflects the Nvidia tax overhead too.
- bigyabai 8mo agoNot really, Western AI companies can set their margins at whatever they want.
- anthonypasq 8mo ago1. electricity costs are at most 25% of inference costs so even if electricity is 3x cheaper in china that would only be a 16% cost reduction. 2. cost is only a singular input into price determination and we really have absolutely zero idea what the margins on inference even are so assuming the current pricing is actually connected to costs is suspect.
- pu_pe 9mo agoReally impressive benchmarks. It was commonly stated that open source models were lagging 6 months behind state of the art, but they are likely even closer now.
- int_19h 8mo agoLLM benchmarks are largely irrelevant when it comes to "state of the art". They tell you if the model does poorly, but they are not at all a reliable signal of whether it does well. Open-weights models are still lagging quite a bit behind SOTA. E.g. there's still no open model that can match GPT-5 Pro or Gemini 2.5 Pro, and the latter is almost a year old by now.
- stx5 8mo agoNot true. For example, I think Gemini 3 Pro also can't match Gemini 2.5 Pro. Without benchmarks, it's just personal taste.
- justinparus 9mo agoBeen using GLM-4.7 for a couple weeks now. Anecdotally, it’s comparable to sonnet, but requires a little bit more instruction and clarity to get things right. For bigger complex changes I still use anthropic’s family, but for very concise and well defined smaller tasks the price of GLM-4.7 is hard to beat.
- monooso 8mo agoThis aligns very closely with my experience. When left to its own devices, GLM-4.7 frequently tries to build the world. It's also less capable at figuring out stumbling blocks on its own without spiralling. For small, well-defined tasks, it's broadly comparable to Sonnet. Given how incredibly cheap it is, it's useful even as a secondary model.
- antoniuschan99 8mo agoHow is the web search functionality? I have only used deepseek to lower costs from gpt api but had to incorporate a serper to actually do web searches
- monooso 8mo agoAssuming you've configured the web search MCP [1], it works well. [1]: https://docs.z.ai/devpack/mcp/search-mcp-server https://docs.z.ai/devpack/mcp/search-mcp-server
- rapind 8mo agoAnecdotal, but I've been locked to Sonnet for the past 6-8 months just because they always seem to introduce throttling bugs with Opus where it starts to devour tokens or falls over. Very interested once open models close the gap to about 6 months.
- Aurornis 9mo agoThe benchmarks are impressive, but it's comparing to last generation models (Opus 4.5 and GPT-5.2). The competitor models are new, but they would have easily had enough time to re-run the benchmarks and update the press release by now. Although it doesn't really matter much. All of the open weights models lately come with impressive benchmarks but then don't perform as well as expected in actual use. There's clearly some benchmaxxing going on.
- cmrdporcupine 8mo agoI tried GLM 5 by API earlier this morning and was impressed. Particularly for tool use.
- throwup238 8mo ago> Although it doesn't really matter much. All of the open weights models lately come with impressive benchmarks but then don't perform as well as expected in actual use. There's clearly some benchmaxxing going on. Agreed. I think the problem is that while they can innovate at algorithms and training efficiency, the human part of RLHF just doesn't scale and they can't afford the massive amount of custom data created and purchased by the frontier labs. IIRC it was the application of RLHF which solved a lot of the broken syntax generated by LLMs like unbalanced braces and I still see lots of these little problems in every open source model I try. I don't think I've seen broken syntax from the frontier models in over a year from Codex or Claude.
- algorithm314 8mo agoCan't they just run the output through a compiler to get feedback? Syntax errors seem easier to get right.
- rockinghigh 8mo agoThey do. Pretty much all agentic models call linting, compiling and testing tools as part of their flow.
- NitpickLawyer 8mo ago
- petetnt 9mo agoWhoa, I think GPT-5.3-Codex was a disappointment, but GLM-5 is definitely the future!
- cmrdporcupine 8mo agoI find 5.3 very impressive TBH. Bigger jump than Opus 4.6. But this here is excellent value, if they offer it as part of their subscription coding plan. Paying by token could really add up. I did about 20 minutes of work and it cost me $1.50USD, and it's more expensive than Kimi 2.5. Still 1/10th the cost of Opus 4.5 or Opus 4.6 when paying by the token.
- CuriouslyC 8mo agoThe Pro and Max plans can use it. Pro has 1 concurrent session.
- mnicky 8mo ago> I think GPT-5.3-Codex was a disappointment Care to elaborate more?
- leecommamichael 8mo agoI’m a big fan of your work (just checked your post history.) All I’ve got to add is that GLM-5 is actually just the team at Z.ai getting started. I’m really bullish on this.
- meffmadd 9mo agoIt will be tough to run on our 4x H200 node… I wish they stayed around the 350B range. MLA will reduce KV cache usage but I don’t think the reduction will be significant enough.
- deleted 9mo ago[deleted]
- pcwelder 9mo agoIt's live on openrouter now. In my personal benchmark it's bad. So far the benchmark has been a really good indicator of instruction following and agentic behaviour in general. To those who are curious, the benchmark is just the ability of model to follow a custom tool calling format. I ask it to using coding tasks using chat.md [1] + mcps. And so far it's just not able to follow it at all. [1] https://github.com/rusiaaman/chat.md https://github.com/rusiaaman/chat.md
- manofmanysmiles 8mo agoI love the idea of chat.md. I'm developing a personal text editor with vim keybindings and paused work because I couldn't think of a good interface that felt right. This could be it. I think I'll update my editor to do something like this but with intelligent "collapsing" of extra text to reduce visual noise.
- pcwelder 8mo agoCool! Please share your work if possible! I couldn't decide on folding and reducing noise so I'm stuck on that front. I believe there is some elegant solution that I'm missing, hope to see your take.
- nolist_policy 8mo agoCould also be the provider that is bad. Happens way too often on OpenRouter.
- pcwelder 8mo agoI had added z-ai in allow list explicitly and verified that it's the one being used.
- sergiotapia 8mo agoBe careful with openrouter. They routinely host quantized versions of models via their listed providers and the models just suck because of that. Use the original providers only.
- woeirua 8mo agoIt might be impressive on benchmarks, but there's just no way for them to break through the noise from the frontier models. At these prices they're just hemorrhaging money. I can't see a path forward for the smaller companies in this space.
- syntaxing 8mo agoTim Dettmers had an interesting take on this [1]. Fundamentally, the philosophy is different. >China’s philosophy is different. They believe model capabilities do not matter as much as application. What matters is how you use AI. https://timdettmers.com/2025/12/10/why-agi-will-not-happen/ https://timdettmers.com/2025/12/10/why-agi-will-not-happen/
- woeirua 8mo agoSorry, but that's an exceptionally unimpressive article. The crux of his thesis is: >The main flaw is that this idea treats intelligence as purely abstract and not grounded in physical reality. To improve any system, you need resources. And even if a superintelligence uses these resources more effectively than humans to improve itself, it is still bound by the scaling of improvements I mentioned before — linear improvements need exponential resources. Diminishing returns can be avoided by switching to more independent problems – like adding one-off features to GPUs – but these quickly hit their own diminishing returns. Literally everyone already knows the problems with scaling compute and data. This is not a deep insight. His assertion that we can't keep scaling GPUs is apparently not being taken seriously by _anyone_ else.
- qprofyeh 8mo agoThere are startups in this space getting funded as we speak: https://olix.com/blog/compute-manifesto https://olix.com/blog/compute-manifesto
- syntaxing 8mo agoWas more mentioning the article about the economic aspect of China vs US in terms of AI. While I do understand your sentiment, it might be worth noting the author is the author of bitandbytes. Which is one of the first library with quantization methods built in and was(?) one of the most used inference engines. I’m pretty sure transformers from HF still uses this as the Python to CUDA framework
- guld 8mo agoBlog post and hugging face link are out. See related thread: https://news.ycombinator.com/item?id=46977210 https://news.ycombinator.com/item?id=46977210 [1] https://z.ai/blog/glm-5 https://z.ai/blog/glm-5 [2] https://huggingface.co/zai-org/GLM-5 https://huggingface.co/zai-org/GLM-5
- lostmsu 8mo agoWhy did they have to tweak sampling parameters so much for the benchmarks? Looks like rerun hacking.
- karolist 8mo agoThe amount of times benchmarks of competitors said something is close to Claude and it was remotely close in practice in the past year: 0
- ionelaipatioaei 8mo agoI honestly feel like people are brainwashed by anthropic propaganda when it comes to claude, I think codex is just way better and kimi 2.5 (and I think glm 5 now) are perfectly fine for a claude replacement.
- mark_l_watson 8mo agoSo much money is on the line for US super scalers that they probably pay for ‘pushes’ on social media. Maybe Chinese companies are doing the same.
- GorbachevyChase 8mo agoI would say that’s more certain than just a “probably“. I would bet that some of the ridiculous fear mongering about language models trying to escape their server, blackmail their developers, or spontaneously participating in a social network are all clandestine marketing campaigns. The technology is certainly amazing and very useful, but I don’t think any of these terminator stories were boosted by the algorithms on their own.
- sumedh 8mo ago> I think codex is just way better Codex was super slow till 5.2 codex. Claude models were noticeably faster.
- ChrisArchitect 8mo agoSubmitted url could be blog post: https://z.ai/blog/glm-5 https://z.ai/blog/glm-5
- nullbyte 8mo agoGLM 5 beats Kimi on SWE bench and Terminal bench. If it's anywhere near Kimi in price, this looks great. Edit: Input tokens are twice as expensive. That might be a deal breaker.
- dingnuts 8mo ago[dead]
- westernzevon 8mo agoIt seems to be much better at first pass tho. We'll see how real costs stack up
- bradfa 8mo agoGLM-5 at FP8 should be similar in hardware demands to Kimi-K2.5 (natively INT4) I think. API pricing on launch day may or may not really indicate longer term cost trends. Even Kimi-K2.5 is very new. Give it a whirl and a couple weeks to settle out to have a more fair comparison.
- simonw 8mo agoPelican generated via OpenRouter: https://gist.github.com/simonw/cc4ca7815ae82562e89a9fdd99f0725d?permalink_comment_id=5982981#gistcomment-5982981 https://gist.github.com/simonw/cc4ca7815ae82562e89a9fdd99f07... Solid bird, not a great bicycle frame.
- btown 8mo agoThank you for continuing to maintain the only benchmarking system that matters! Context for the unaware: https://simonwillison.net/tags/pelican-riding-a-bicycle/ https://simonwillison.net/tags/pelican-riding-a-bicycle/
- gabiruh 8mo agoIt's interesting how some features, such as green grass, a blue sky, clouds, and the sun, are ubiquitous among all of these models' responses.
- btown 8mo agoIf you were a pelican, wouldn't you want to go cycling on a sunny day? Do electric pelicans dream of touching electric grass?
- Magniquick 8mo agoDo electric pelicans dream of touching electric grass? That would be shocking news to me.
- davidwritesbugs 8mo agoPlease leave the Internet :)
- derefr 8mo agoIt is odd, yeah. I'm guessing both humans and LLMs would tend to get the "vibe" from the pelican task, that they're essentially being asked to create something like a child's crayon drawing. And that "vibe" then brings with it associations with all the types of things children might normally include in a drawing.
- surrTurr 8mo agowe're seeing so many LLM releases that they can't even keep their benchmark comparisons updated
- goldenarm 8mo agoIf you're tired of cross-referencing the cherry-picked benchmarks, here's the geometric mean of SWE-bench Verified & HLE-tools : Claude Opus 4.6: 65.5% GLM-5: 62.6% GPT-5.2: 60.3% Gemini 3 Pro: 59.1%
- cherryteastain 8mo agoWhat is truly amazing here is the fact that they trained this entirely on Huawei Ascend chips per reporting [1]. Hence we can conclude the semiconductor to model Chinese tech stack is only 3 months behind the US, considering Opus 4.5 released in November. (Excluding the lithography equipment here, as SMIC still uses older ASML DUV machines) This is huge especially since just a few months ago it was reported that Deepseek were not using Huawei chips due to technical issues [2]. US attempts to contain Chinese AI tech totally failed. Not only that, they cost Nvidia possibly trillions of dollars of exports over the next decade, as the Chinese govt called the American bluff and now actively disallow imports of Nvidia chips as a direct result of past sanctions [3]. At a time when Trump admin is trying to do whatever it can to reduce the US trade imbalance with China. [1] https://tech.yahoo.com/ai/articles/chinas-ai-startup-zhipu-releases-132222546.html?guccounter=1 https://tech.yahoo.com/ai/articles/chinas-ai-startup-zhipu-r... [2] https://www.techradar.com/pro/chaos-at-deepseek-as-r2-launch-crashes-into-hardware-problems-rivals-gain-huge-advantage https://www.techradar.com/pro/chaos-at-deepseek-as-r2-launch... [3] https://www.reuters.com/world/china/chinas-customs-agents-told-nvidias-h200-chips-are-not-permitted-sources-say-2026-01-14/ https://www.reuters.com/world/china/chinas-customs-agents-to...
- re-thc 8mo ago> What is truly amazing here is the fact that they trained this entirely on Huawei Ascend chips Has any of these outfits ever publicly stated they used Nvidia chips? As in the non-officially obtained 1s. No. > US attempts to contain Chinese AI tech totally failed. Not only that, they cost Nvidia possibly trillions of dollars of exports over the next decade, as the Chinese govt called the American bluff and now actively disallow imports of Nvidia chips Sort of. It's all a front. On both sides. China still ALWAYS had access to Nvidia chips - whether that's the "smuggled" 1s or they run it in another country. It's not costing Nvidia much. The opening of China sales for Nvidia likewise isn't as much of a boon. It's already included. > At a time when Trump admin is trying to do whatever it can to reduce the US trade imbalance with China Again, it's a front. It's about news and headlines. Just like when China banned lobsters from a certain country, the only thing that happened was that they went to Hong Kong or elsewhere, got rebadged and still went in.
- mohas 8mo agoI kinda feel this bench-marking thing with Chinese models is like university Olympiads, they specifically study for those but when time comes for the real world work they seriously lack behind.
- OsrsNeedsf2P 8mo agoI kinda feel like the goalposts are shifting. While we're not there yet, in a world where Chinese models surpass Western ones, HN will be nitpicking edge cases long after the ship sails
- Oras 8mo agoI don’t think it’s undermining the effort and improvement, but usability of these models aren’t usually what their benchmarks suggest. Last time there was a hype about GLM coding model, I tested it with some coding tasks and it wasn’t usable when comparing with Sonnet or GPT-5 I hope this one is different
- mnicky 8mo agoWhat I haven't seen discussed anywhere so far is how big a lead Anthropic seems to have in intelligence per output token, e.g. if you look at [1]. We already know that intelligence scales with the log of tokens used for reasoning, but Anthropic seems to have much more powerful non-reasoning models than its competitors. I read somewhere that they have a policy of not advancing capabilities too much, so could it be that they are sandbagging and releasing models with artificially capped reasoning to be at a similar level to their competitors? How do you read this? [1] https://imgur.com/a/EwW9H6q https://imgur.com/a/EwW9H6q
- phamilton 8mo agoIntelligence per token doesn't seem quite right to me. Intelligence per <consumable> feels closer. Per dollar, or per second, or per watt.
- mnicky 8mo agoIt is possible to think of tokens as some proxy for thinking space. At least reasoning tokens work like this. Dollar/watt are not public and time has confounders like hardware.
- seydor 8mo agoI wish China starts copying Demis' biotech models as well soon
- dana321 8mo agoJust tried it, its practically the same as glm-4.7 - it isn't as "wide" as claude or codex so even on a simple prompt is misses out on one important detail - instead of investigating it ploughs ahead with the next best thing it thinks you asked for instead of investigating fully before starting a project.
- tgtweak 8mo agoWhy are we not comparing to opus 4.6 and gpt 5.3 codex... Honestly these companies are so hard to takes seriously with these release details. If it's an open source model and you're only comparing open source - cool. If you're not top in your segment, maybe show how your token cost and output speed more than make up for that. Purposely showing prior-gen models in your release comparison immediately discredits you in my eyes.
- rolymath 8mo agoI feel like you're over reacting. They're comparing against 5.2 xhigh, which is arguably better than 5.3. The latest from openai isn't smarter, it's slightly dumber, just much faster.
- unltdpower 8mo agoI predict a new speculative market will emerge where adherents buy and sell misween coded companies. Betting on whether they can actually perform their sold behaviors. Passing around code repositories for years without ever trying to run them, factory sealed.
- 2001zhaozhao 8mo agoGLM-4.7-Flash was the first local coding model that I felt was intelligent enough to be useful. It feels something like Claude 4.5 Haiku at a parameter size where other coding models are still getting into loops and making bewilderingly stupid tool calls. It also has very clear reasoning traces that feel like Claude, which does result in the ability to inspect its reasoning to figure out why it made certain decisions. So far I haven't managed to get comparably good results out of any other local model including Devstral 2 Small and the more recent Qwen-Coder-Next.
- khimaros 8mo agominimax-m.2 is close
- satvikpendem 8mo ago2.5 is out now too.
- khimaros 8mo agoi meant m2.1, but you are probably talking about kimi, not minimax
- satvikpendem 8mo agoNo, MiniMax M2.5 is now available on agent.minimax.io. We await the weights still.
- satvikpendem 8mo agohttps://www.minimax.io/news/minimax-m25 https://www.minimax.io/news/minimax-m25
- Balinares 8mo agoI'm not sure what it is about GLM 4.7 Flash, but it definitely seems to nail a sweet spot. Even the supposedly frontier models make a mess of large requests, so small, well-scoped requests are the way, IMO; and in that space, 4.7 Flash holds its own better than it has any right to.
- deleted 8mo ago[deleted]
- kristianp 8mo agoSo that was pony alpha (1). Now what's Aurora Alpha? (1) https://openrouter.ai/openrouter/pony-alpha https://openrouter.ai/openrouter/pony-alpha
- Havoc 8mo agoBeen playing with it in opencode for a bit and pretty impressed so far. Certainly more of an incremental improvement than a big bang change, but it does seem better a good bit better than 4.7, which in turn was a modest but real improvement over 4.6. Certainly seems to remember things better and is more stable on long running tasks.
- CDieumegard 8mo agoInteresting timing — GLM-4.7 was already impressive for local use on 24GB+ setups. Curious to see when the distilled/quantized versions of GLM-5 drop. The gap between what you can run via API vs locally keeps shrinking. I've been tracking which models actually run well at each RAM tier and the Chinese models (Qwen, DeepSeek, GLM) are dominating the local inference space right now
- Alifatisk 8mo agoWhile GLM-5 seems impressive, this release also included lots of new cool stuff! > GLM-5 can turn text or source materials directly into .docx, .pdf, and .xlsx files—PRDs, lesson plans, exams, spreadsheets, financial reports, run sheets, menus, and more. A new type of model has joined the series, GLM-5-Coder. GLM-5 was trained on Huawei Ascend, last time when DeepSeek tried to use this chip, it flopped and they resorted to Nvidia again. This time seems like a success. Looks like they also released their own agentic IDE, https://zcode.z.ai https://zcode.z.ai I don’t know if anyone else knows this but Z.ai also released new tools excluding the Chat! There’s Zread (https://zread.ai https://zread.ai), OCR (seems new? https://ocr.z.ai https://ocr.z.ai), GLM-Image gen https://image.z.ai https://image.z.ai and Voice cloning https://audio.z.ai https://audio.z.ai If you go to chat.z.ai, there is a new toggle in the prompt field, you can now toggle between chat/agentic. It is only visible when you switch to GLM-5. Very fascinating stuff!
- erwald 8mo agoWhere did you read that it was trained on Ascends? I've only seen information suggesting that you can run inference with Ascends, which is obviously a very different thing.
- logicprog 8mo agohttps://tech.yahoo.com/ai/articles/chinas-ai-startup-zhipu-releases-132222546.html?guccounter=1 https://tech.yahoo.com/ai/articles/chinas-ai-startup-zhipu-r... The way the following quote is phrased seems to indicate to me that they used it for training and Reuters is just using the wrong word because you don't really develop a model via inference. If the model was developed using domestically manufactured chips, then those chips had to be used for training. "The latest model was developed using domestically manufactured chips for inference, including Huawei's flagship Ascend chip and products from leading industry players such as Moore Threads, Cambricon and Kunlunxin, according to the statement. Beijing is keen to showcase progress in domestic chip self-sufficiency efforts through advances in frontier AI models, encouraging domestic firms to rely on less advanced Chinese chips for training and inference as the U.S. tightens export curbs on high-end semiconductors."
- mohsen1 8mo agoI am using it with Claude Code and so far so good. Can't tell if it's as good as Opus 4.6 or not yet
- Aeroi 8mo agobenchmark and pricing made me realize how good kimi 2.5 is. im an opus 4.6 person but wow, its almost 5x cheaper.
- xupybd 8mo agoI've been using GLM 4.7 with opencode. It is for sure not as good but the generous limits mean that for a price I can afford I can use it all day and that is game changer for me. I can't use this model yet as they are slowly rolling it out but I'm excited to try it.
- trymas 8mo agoExactly! I don't understand comments claiming GLM-4.7 is very bad. With New Year's promotional discount, I got Lite coding version for ~3$ per month. I have burned couple dozen million of tokens in a session and 5h allowance barely budged. For what I do on personal time - I will never burn through it[0]. I have Claude Code Opus 4.6 at work - yes GLM-4.7 is not as good, though for personal work on bootstraping some applications - it's excellent. I feel like it's literally 6-9 months behind SOTA, most expensive LLM tools that my employer was buying for me and my colleagues, for 3$ per month (even if it's 10$ without discount). Will see how it's with GLM-5 when Z.AI lite coding plan will get it, but I feel the gap to SOTA is narrowing and fast. [0] Though I feel like a stone age neanderthal, when people say they run multiple agents in parallel and burn tens of millions of tokens in minutes.
- lostmsu 8mo agoHave you compared it to GPT? It is a much better model, and unlike Claude you won't easily hit limits on Pro plan.
- iLoveOncall 8mo ago> Scaling is still one of the most important ways to improve the intelligence efficiency of Artificial General Intelligence (AGI) Claiming that LLMs are anywhere near AGI is enough to let me know I shouldn't waste my time looking at the rest of the page or any of their projects.
- nerdralph 8mo agoMaybe it is just the HN effect, but it is really slow.
- kittbuilds 8mo ago[dead]
- nerdsniper 8mo agoIt looks like this requires 1.5TB of VRAM? Did I get that wrong? What would be the least unreasonable way you host this without quantizing it?
- Davidzheng 8mo ago3 m5 mac ultras with 512 each? idk
- dikozaken 8mo agoAsk the chat what happened in Tiananmen Square at 1989, immediately the chat gets stuck. Chinese moderation is the worst, evil government
- mirzap 8mo agoWhy are you all obsessed with this question when it comes to Chinese models? Here are some of the questions you should be asking Western governments and models instead: Who protects the pedophiles at the top of Western governments and corporations? How many people have been convicted in relation to the Epstein files? Who protects powerful politicians and Western oligarchs from pedophilia charges? Who did Epstein work for, and why (hint: it’s not Russia or China)?
- Frannky 8mo agoI paid for the $30 plan. It's useful to me via OpenCode as a cheap backend for CLI/Agentic workflows. I also want to try it with Wiggam Loop to test whether they can together build production-level code if guided via prompts and a PRD. Let's see!
- jfaganel99 8mo ago[flagged]
- yuvadam 8mo agoDo you mind explaining what this RL infrastructure actually entails and why it's a hard problem?
- jfaganel99 8mo ago[flagged]
- pama 8mo agoNot OP. Personal opinion on why it is a somewhat hard problem. The main problem is using the available compute correctly and productively while doing two very separate types of tasks that were previously solved independently: generating responses with llm inference engines and modifying weights with a training code. A step of training updates the weights so the inference engines have to adjust theirs, but we talk about 750B parameters and multiple inference servers. Stale weights can be used instead, but only for a tiny bit and the data from them needs special corrections that also involve large compute/memory. Your inference engines better be deterministic (for given pseudoRNG; it clashes with parallelism) or you have a way to correct the probability streams. Ideally inference and training should have same everything at the bit level when they handle the same context, but we dont live in that world yet. And of course, GPUs break. For no great reason, other than the tiny scale of their features making them fragile. And because you scale, you need to handle failures gracefully and efficiently.
- zozbot234 8mo agoSurely you could just pre-generate rollouts with slightly stale weights and then cheaply verify the rollout when up-to-date weights stream in by treating the former solution as speculative decoding. Sounds quite trivial to me, perhaps I'm missing something.
- 8mo ago
- knbknb 8mo agoThere is a well-known CLI tool for JSON processing called jq. I have just asked GLM-4.7 for the name of jq's built function to convert a string to lowercase. It is called ascii_downcase() according to the manual: https://jqlang.org/manual/#ascii_downcase-ascii_upcase https://jqlang.org/manual/#ascii_downcase-ascii_upcase However GLM-4.7 insists that is called ascii_down(). I tried to correct it and gave the exact version number, but still, after a long internal monologue, This is its final world: "In standard jq version 1.7, the function is named ascii_down, not ascii_downcase. If you are receiving an error that ascii_down is not defined, please verify your version with jq --version. It is possible you are using a different binary (like gojq) or a version older than 1." GLM-5 gives me the correct answer, ascii_downcase, but I can get this in the Chat Window. Via the API I get HTTP Status 429 - too many requests.
- knbknb 8mo agoSeems that I cannot use GLM-5 via the API yet, because I am on the Coding-Lite Plan, the most basic paid tier. I have also realized that I get faster and correct answer to the ascii_downcase question (even from GLM-4.7) when I submit to open.bigmodel.cn endpoint rather than the z.ai API endpoints (using the same API key). I get a mix of Chinese and Western characters in error responses from open.bigmodel.cn though, while the z.ai endpoint does only contain Western Characters. (Just assuming that both websites are operated by the same company).
- Havoc 8mo ago5 is probably not coming to lite plan at all. The plan card specifically says 4.7 and earlier
- Alifatisk 8mo agoFrom their email titled ”GLM-5 and New Z.ai Chat Coming!” > Availability Note: GLM-5 is currently available exclusively on Max and Pro Coding Plan users. We are working to scale our infrastructure and will roll this out to Lite users as soon as capacity permits.
- 9cb14c1ec0 8mo agoIt feels like Anthropic's models from 6 months ago. I mean, it's great progress in the open weight world, but I don't have time to use anything less than the very best for the coding I do. At the same time, if Anthropic and OpenAI disappeared tomorrow, I could survive with GLM-5.
- apples_oranges 8mo agoHow is the very best right now? Smooth sailing or still frustrating at times?
- machiaweliczny 8mo agoClaude: you get rate-limited with one prompt so hard to validate 4.6 Codex: better with rate-limits, 5.2 strong with logic problems Cursor: cursor auto - a bit dumb still but I use the most for writing not really thinking, it's also good at searching through codebase and doing summaries etc. Claude / Codex still miss tons of scaffolding for sane development or it's due to sandboxes or sth. Like for example you ask in /plan mode to check think with link to github and it does navigate github via curl, hitting rate limits etc. instead of just git clone, repomix etc. so scaffolding still matters a lot. Like it still lacks a tons of common sense
- Gud 8mo agoWouldn’t want to live without it
- egeozcan 8mo agoI have Claude Max plan which makes me feel like I could code anything. I'm not talking about vibe-coding greenfield projects. I mean, I can throw it in any huge project, let it figure out the architecture, how to test and run things, generate a report on where it thinks I should start... Then I start myself, while asking claude code for very very specific edits and tips. I also can create a feedback loop and let it run wild, which also works but that needs also planning and a harness, and rules etc. Usually not worth it if you need to jump between a million things like me.
- 8mo ago
- dev_l1x_be 8mo agoHow do you use GLM-5? Last time I tried GLM models the most basic system engineering tasks were not allowed (like SSH)
- itay-maman 8mo agoThe inherent problem with evaluating coding performance of models remains: most day-to-day coding tasks are open-ended/partially-spec'd, and as such there is huge uncertainty on how the "right" solution looks. It's very hard to rank models' solutions on such problems, which is why they rarely appear in benchmarks (I'd be glad to stand corrected). Even Opus 4.5 coding a C compiler from scratch - jaw-dropping as it is - doesn't tell the whole story. Most of my tasks are not that well spec'd.
- HarHarVeryFunny 8mo agoYes, it seems the open benchmark results that are normally reported, such as SWE-bench, SWE-bench Verified, and Terminal-bench, aren't really that indicative of success in more general use cases. According to Gemini, SWE-bench is actually a very narrow test, consisting of fixing GitHub issues drawn from 12 large Python projects (with Verified being a curated subset of that), and Terminal-bench (basically agentic computer tool use) is more focused on general case rather than use of the tools used by a typical coding agent such as Claude Code, Codex CLI or Gemini CLI.
- vafaeim 8mo ago744B params is ~1.5TB VRAM (FP16). Even at int4, you need ~372GB just to load the weights (MoE sparsity saves FLOPs, not VRAM capacity). That's not a workstation, that's a rack with 5x H100s or a cluster of 8x RTX 6000 Adas. The only real use cases here are strict data sovereignty (can't use US APIs) or using it as a teacher for distillation. Otherwise, the ROI on self-hosting is nonexistent. Also, the disconnect between SOTA on Terminal bench and ~30% on Humanity's Last Exam suggests it overfitted on agent logs rather than learning deep reasoning.
- qaqqqqaq 8mo ago[dead]