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Ox-Alpha Is GLM?
- volf_ 23d agoGLM 5.3 and all previous models don't have a vision encoder and can only accept text. Ox-Alpha can accept video and images, so unless Z-ai added a pretty good vision encoder for this model, I don't think so. My money is on Moonshot and this being Kimi K3.5. The measured tps and latency is in-line with K3's tps and latency from Moonshot. MiniMax M3.5 is also possible (but the MiniiMax provider is a lot more performant than the lab behind ox-alpha, so less likely).
- Almondsetat 23d agoDeepSeek literally just came out with the vision-enabled version of Flash v4 which was purely text based. Why would GLM not be able to do the same thing?
- volf_ 23d agoIt's possible
- Bolwin 23d agoGlm had made vision models in the past. Look up GLM 5v. The only question now is if it's 5.3v, 5.4/5.5 or a dedicated flash/vision model
- volf_ 23d agoYeah. It could be. The Z.ai DC latency is still ~1.2s faster than whomever is serving this model.
- BoredomIsFun 23d agoGLM made pretty decent for that time small 9b vision model, GLM-4.1.
- nylonstrung 23d agoIt would be stranger to me that Kimi switched to GLM's tokenizer than that GLM added multimodal like Kimi and Deepseek both did recently
- minimaxir 23d agoThe other tell from the provider angle is capacity. Whoever is hosting Ox Alpha has a lot of capacity which narrows down a lot of the Chinese companies.
- TiredOfLife 23d agoBut Moonshot limited signups because they lacked compute.
- Havoc 23d ago> and all previous models They have had vision models before just not their flagships
- ggcr 23d agoZ.ai founders were one of the pioneers in MM-LLMs with Cog-VLM years ago, back when LLaVA emerged. I wouldn't be surprised if they added multi-modal capabilities
- ricardobeat 22d agoI hope this is not Kimi K3.5 because it really sucks. It is very slow, not particularly smart when it comes to coding, and easily starts going in circles - when not straight up going into a doom loop.
- ChrisArchitect 23d agoRelated: Ox Alpha https://news.ycombinator.com/item?id=49381896 https://news.ycombinator.com/item?id=49381896
- xorgun 23d agoDont rule out ssi
- nullbio 23d agoThat would be insanely disappointing.
- behnamoh 23d ago[flagged]
- minimaxir 23d agoYou cannot "dox" an AI model. Given the traction the model has received, it is extremely newsworthy to know who's developing and hosting it.
- behnamoh 23d agomy question is: how does that affect a company's strategy? it's not like management is gonna switch models soon as a new shiny one drops. entire workflows depend on specific models working the way they do; you can't just swap out models.
- volf_ 23d agosame business model as crack. best way to get people hooked is to make the first hits free.
- minimaxir 23d agoIf it's a really really good model, then yes, people will switch as long as the price is right. Ox Alpha is looking to be a really really good model to the point that it competes with Fable/Sol, and will likely beat them on price.
- JSR_FDED 23d agoYou can learn from the variety of techniques they used to come to this conclusion.
- walrus01 23d agoI wasn't aware that an inanimate piece of software run by a corporation can be 'doxxed'. Totally inaccurate use of the neologism.
- tjwebbnorfolk 23d ago> so much time on your hands Yet here you are, reading AND commenting about it
- jerrythegerbil 23d agoAs someone who uses NCD nearly every day, I have concerns about how it’s been used here. But while we’re “guessing”: Xiaomi MiMO
- walrus01 23d agoHave also seen people guess it's a next version of Longcat, but I also think that's unlikely
- dejanseo 23d agoAuthor here. Tell me more. How do you use NCD and what is your concern about its application here? Should I have use da larger reference sample? You can test it in action here: https://dejan.ai/tools/ai/ https://dejan.ai/tools/ai/ (e.g. drop a claude article or GLM article in and see what it says, it's not perfect but reasonably good).
- dejanseo 21d agoPS: https://z.ai/blog/glm-5.3-flash https://z.ai/blog/glm-5.3-flash
- gvkhna 23d agoIf it’s not zhipu then why is it returning errors that zhipu does for other models? Who else would return the exact same errors even if they took a lot of core infra like tokenizer from z?
- e9 23d agoSomeone could've trained model on top of GLM. Same way Cognition trained their SWE model on top of Kimi and Cursor did same with their Composer model.
- gvkhna 23d agoWhile possible the amount of variation in serving infrastructure is unlikely to land with actually giving the exact same errors zhipu does. It feels like glm flash, and there was a report zhipu had secured a huge new cluster suggesting they have the capacity. My guess anyway. https://www.tomshardware.com/tech-industry/artificial-intelligence/z-ai-powers-up-1gw-ai-data-center-built-entirely-on-chinese-chips https://www.tomshardware.com/tech-industry/artificial-intell...
- vitorgrs 23d agoThe reasoning levels are the same as GLM 5.3. GLM 5.3 is still not open... I believe it's GLM 5.3 Flash or Air.
- weiran 23d agoReasoning levels are often just injected system prompts so not a great way to fingerprint models.
- eli 22d agoBut it's an error, not a response.
- ggcr 23d agoZiphu has that many resources to be able to serve capacity for 1 quadrillion tokens per day on Nous portal? My bet is that it's a Composer model from Cursor running on xAI cluster, they already did a Composer based on Kimi-K2.5
- mogili 23d agoIt's not a good model tbh, got a bunch of things wrong that Opus corrected in my codebase.
- petesergeant 23d agoYet to find a model that cross-model review doesn’t find a bunch of things wrong with. I’m running simultaneous review with whichever of Grok4.6/GLM5.3/Fable/Sol didn’t write it, and each model tends to find items the others didn’t.
- gvkhna 23d agoThe harness is making a big difference, lackluster performance with pi but somehow very good performance with opencode. There’s some rl there for sure, for a smaller model it’s likely going to perform much better in a harness it understands the best.
- SyneRyder 23d agoI've been using a harness that I made myself, and making improvements to the harness has vastly improved its performance. It's actually been a useful model to identify flaws in the harness. I think something also went wrong with the Ox provider last night (at least on OpenRouter), for a few hours it wouldn't accept tools. Zero change to the harness while I slept and it was back working again the next morning.
- petesergeant 23d agoI think within 12 months we’re going to see a frontier (inc open models) that’s so good at almost all human-directed tasks that which model you use just won’t matter. Only differences that remain will be in deep research or very long-range tasks.
- stingraycharles 23d agoPeople were saying this last year, and they’ll be saying the exact same thing next year. The goalpost keeps moving.
- Tepix 23d agoIt‘s already happening, people are using cheaper models because they are good enough
- petesergeant 23d agoSomeone else having been too early on a prediction has little bearing on my prediction. A year ago almost nobody was using open models as daily drivers, today they are. When I run out of Fable and Sol credits in a week, I switch to GLM5.3, and it's not quite there, but it's good enough for productive work.
- tadkar 23d agoI wonder if the NCD metric says something about distillation too. Would you expect that a model that has been distilled/seen traces from other models would have a smaller NCD? It would be really interesting to see if this holds up and provides evidence of distillation or certainly evidence of model outputs being used in the training mix.
- krackers 23d agohttps://eqbench.com/results/creative-writing-v3/hybrid_parsimony/charts/ox-alpha__phylo_tree_parsimony_rectangular.png https://eqbench.com/results/creative-writing-v3/hybrid_parsi...
- dejanseo 23d agoThis looks spot on, where is it from?
- dejanseo 23d agoHello! I wrote the above article and did the NCD on model outputs. The same thought crossed my mind when I saw Gemma misclassified as Gemini quite frequently. And GLM almost as Claude and not as Gemini at all. Gave me the feeling as if GLM didn't train on Gemini generated synthetic data at all but mainly on Claude and GPT.
- try-working 23d agoNvidia
- Zylokloto 22d agoNvidia is quite open in publishing and talking about their models though.
- deleted 23d ago[deleted]
- swiftcoder 23d ago> How many words are in the previous message? Its amazing to me that providers haven't added any sort of masking of the prompt in the thinking traces to avoid prompt extraction via this sort of trivial attack
- dejanseo 23d agoHey, it may be trivial, I'm pretty proud of it :)
- pijalu 23d agoMy bet: it's Google running a "new" model based on GLM
- simianwords 23d agoInteresting. I like this theory because it explains why some G employees were vague posting about it. But like.. why? Why wouldn’t Google just use Gemma?
- re-thc 23d ago> why some G employees were vague posting about it They were just trolling.
- Zylokloto 22d agoThat would be a complete defeat for a Frontierlab / Company like Google/Deepmind. They will never ever do like this. They for sure would add architecture ideas from other research/models but thats it.
- simianwords 23d agoMy strong prediction: this model is around 64B and can run on laptops. Thats the reason behind the hype.
- anon373839 23d agoIt's fun to imagine that it could be GLM 5.3-Flash. Between GLM 4 and 5, the flagship's total parameters doubled and the active parameters went up 25%. GLM 4.7-Flash was 30B / 3B active. If this model were 60B / 4B active, that sure would hit a sweet, currently empty spot in the lineup of open models. But I don't know. There are vagueposts on X about this model running on two DGX Sparks. If they did the same scale-up with Air instead of Flash, that would probably be about right.
- re-thc 23d ago> this model is around 64B and can run on laptops. We're lucky if it'd fit in 1 DGX Spark. Laptops - nah, unless you mean like an M5 Max with 128GB of RAM then maybe. > Thats the reason behind the hype. The hype is imagine DeepSeek Flash before the price increase with even better performance. It'd be like unlimited Sonnet.
- Otterly99 23d agoThe Ox-Alpha webpage really make it sound like they are trying to hype a model that has nothing particular to show: "The reasoning model that appeared out of nowhere. Built for code, long-horizon agents, and a million tokens of context. Nobody knows who made it — everyone wants to try it."
- johndough 23d agoOx Alpha is almost certainly a model by Z.ai. https://files.catbox.moe/k52n6k.png https://files.catbox.moe/k52n6k.png The upper chart shows the availability of Ox Alpha and the lower chart shows the availability of GLM 5.3 by Z.ai. They had a blip at exactly the same time.
- troysk 23d agoIt is probably from Google and is probably hosted on Vertex AI. Opencode announced that responses from Ox Alpha should be better and soon posted about Vertex eu and us multi region update in their changelog. I could be a Gemini model or a new one based on GLM based on tokenizer. Also the amount of inference it is providing for free is something only google can support with its TPUs. So maybe a GLM based model running on TPUs.
- walrus01 23d agoI've seen a number of people report that it answers near-identically to mainland CN built models on topics related to controversial things the CCP doesn't want to talk about. I'd be extremely surprised if it's a Google model.
- dezgeg 22d agoI extremely doubt it's Gemini - all previous Geminis have had very different output style from other models. In a coding harness Gemini is extremely quiet and mostly just does thinking and tool calls, with the thinking blocks heavily summarized. Also Claude and the Chinese models really like to say "Let me X", Geminis preference is "I will X".
- troysk 21d agoOther folks were correct and I was wrong! It has come out as GLM 5.3 Flash.
- vladimirmackic 23d ago[dead]
- AndrewDucker 22d agoYes: https://news.ycombinator.com/item?id=49446422 https://news.ycombinator.com/item?id=49446422
- vrighter 20d agoAs far as I'm concerned, GLM is the opengl mathematics library. I wish projects would check before stealing a name.