3 ms·
MiniMax M2.7 Is Now Open Source
- deleted 6mo ago[deleted]
- steveharing1 6mo agoNvidia is providing free API to try Minimax M2.7
- ctdinjeu5 6mo agoFor those who like open source so much they want to use a provider
- exe34 6mo agoCould you explain the incompatibility? These seem like orthogonal axes to me.
- ctdinjeu5 6mo agoJust a joke, but you’re right I can like open source and not want to self host
- avaer 6mo agoI think this is the majority view.
- fifthace 6mo agoIf rumours OpenAI are doing 70% margins on inference and Anthropic doing 30% margins, then open weights models hosted on clouds happy with 10% margins increase competition and decrease cost. I’m game, like most. Much easier compliance with data sovereign concerns too.
- zozbot234 6mo ago> OpenAI are doing 70% margins on inference and Anthropic doing 30% margins That difference is actually pretty surprising. Is Claude that much more expensive to host? The end-user pricing seems to be pretty similar, or better for OpenAI.
- Demiurge 6mo agoIt should be at least cheaper if anyone can host it, no?
- adrian_b 6mo agoWhile I would not use an external provider, that may be a rational choice for some. The most important advantage of using open weights models is to have perfectly predictable performances and costs in the future. When you can run the model on your own hardware you are protected from price increases, subscription limits decreases or quality reductions of the provided models, like it has already happened for the users of Claude Code. The disadvantage is that if you also want a high speed, you need more expensive hardware. You may defer the cost of buying better hardware, if you use an external provider for now, but you keep in reserve the possibility of hosting yourself the models that you are using, if anything makes the external providers worse.
- aand16 6mo agoI'm wondering if anybody actually manages to use a new Nvidia account. After logging into my shiny new Nvidia account, I'm presented with a banner saying "contact support to verify your account at help@build.nvidia.com". I've contacted Nvidia support and haven't heard back. But they did send me a newsletter...
- rvz 6mo agoWith limits. "free" does not mean what you think it means. To Downvoters: I hope you have read the NVIDIA API Trial Terms of Service [0] before signing up. It clearly has restrictions and limitations. From [0]: > Unless you purchase a Subscription from NVIDIA or a Service Provider (as applicable), you may only use the API Service for internal testing and evaluation purposes, not in production. The terms and conditions of your Subscription will govern your production use of the API Service. [0] https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf https://assets.ngc.nvidia.com/products/api-catalog/legal/NVI...
- girvo 6mo agoGGUFs are out too, well done Unsloth as usual! https://huggingface.co/unsloth/MiniMax-M2.7-GGUF https://huggingface.co/unsloth/MiniMax-M2.7-GGUF I've been using M2.7 through the Alibaba coding plan for a bit now, and am quite impressed with it's coding ability, and even more impressed when I see how small it is. Fascinating really, makes me wonder how big the frontier models are.
- wg0 6mo agoAre you talking about this: https://www.alibabacloud.com/help/en/model-studio/coding-plan https://www.alibabacloud.com/help/en/model-studio/coding-pla... How does it compare to z.ai GLM?
- girvo 6mo agoI am! GLM-5 (which is all I have access to on it, not the newer GLM-5.1) is slightly better for the coding tasks I'm using them for, in terms of being more accurate slightly more often. Both are very good, and very close to one another in practice Qwen3.5-plus is also quite excellent: all of these models feel pretty similar to Sonnet 4.5 in practice, though GLM-5 can have "Opus" like reasoning through surprisingly long context chains I've found.
- zozbot234 6mo agoQwen 3.5 is great and openly available, but it seems that Qwen 3.6 will only release smaller models (TBD, but the ~300B size seems to be excluded already).
- girvo 6mo agoYeah I saw. Such a shame, I’m playing with a Q4 version of 3.5 122B-A10B on my Asus GX10, it’s kind of nuts how great a model you can run at home (with limitations of course)
- hulk-konen 6mo agoI think GLM 5.1 is a step above M2.7 and Qwen 3.6. I’ve used it to do some planning when I ran out of Opus usage, and it’s done ok job. Wouldn’t trust it with some more difficult data shape edits etc., but it’s a nice option to have! Composer 2, M2.7, and Qwen 3.6 are all capable to execute those plans just fine.
- jbergqvist 6mo ago"Helped build itself" is a bit of a stretch here, it makes it sound as if the model was doing lasting self-improvements. What the article describes is that the model was able to tweak to its own deployment harness (memory, skills, experimental loop etc) to improve performance on benchmarks. While impressive, it's not doing any modifications to its own weights by e.g. modifying the training code.
- zozbot234 6mo agoBy this standard, Claude "helped build itself" since Claude Code is 100% vibe coded. Not sure if this also applies somewhat to ChatGPT and Codex.
- anonym29 6mo agoIn addition to this conversation already having been started at https://news.ycombinator.com/item?id=47735348 https://news.ycombinator.com/item?id=47735348 yesterday, MiniMax M2.7 is not open source. The open weights have been released, which is definitely good and follows some of the spirit of open source, but isn't the same thing.
- adrian_b 6mo agoWhile an open-source model is obviously preferable to an open-weights model, the difference between the two is much less important than the difference between an open-weights model and a proprietary model. There are much more people who are interested only in doing model inference, for which an open-weights model is sufficient to avoid the uncertainties and costs associated with a subscription, and for enabling them to make and use better model harnesses than those offered commercially (better by being more suitable for their specific needs), than people who also want to do model training, for which an open-source model would be needed.
- anonym29 6mo agoAbsolutely - I'm one of these types of people who just want local inference myself. I have a Strix Halo rig and I'm thrilled to have Minimax M2.7 weights to run locally. Like I said, this is still an unambiguously good thing, and follows some of the spirit of open source. Just know that Minimax M2.7 is offered with a noncommercial license. If you use it for commercial purposes, you may be on the hook, liability-wise.
- simonw 6mo agoAbsolutely not "open source" - here's the license: https://huggingface.co/MiniMaxAI/MiniMax-M2.7/blob/main/LICENSE https://huggingface.co/MiniMaxAI/MiniMax-M2.7/blob/main/LICE... > Non-commercial use permitted based on MIT-style terms; commercial use requires prior written authorization. And calling the non-commercial usage "MIT-style terms" is a stretch - they come with a bunch of extra restrictions about prohibited uses. It's open weights, not open source.
- zozbot234 6mo agoIt's not even open weights as generally understood, the non-commercial restriction is pretty severe. The earlier M2.5 model will still be preferred for many purposes.
- orlp 6mo agoI've flagged the post, the title is editorialized, the title on the blog post is "MiniMax M2.7: The Agentic Model That Helped Build Itself" (at least at the time of writing this).
- zozbot234 6mo ago"Helped build itself" is arguably also a stretch as noted in another comment.
- MarsIronPI 6mo agoEven the MIT-licensed weights are just that: open weights. Let's not call the weights "source", because they're emphatically not. I can't retrain Qwen from the ground up with different pre-training algorithms, for example.
- zozbot234 6mo agoModel weights are source because they are "the preferred form for modification", e.g. you can use them for fine-tuning. Training a new model from raw data (1) gets you something very different from the original and (2) is computationally unfeasible for most, compared to simpler fine tuning.
- wg0 6mo agoIn my experience, even the MiniMax M2.5 is a very capable model with decent capabilities and with some hand holding, can do good investigation into an issue deep down multiple layers of a software stack given you keep asking right questions. I am pretty sure MiniMax M2.7 would be much better.
- fg137 6mo agoWhat's people's experience of using MiniMax for coding? I had a really bad time with it. I use (real) Claude Code for work so I know what a good model feels like. MiniMax's token plan is nice but the quality is really far from Claude models. I needed to constantly "remind" it to get things done. Even for a four sentence prompt in a session that is well below the context window, MiniMax would ignore half of it. This happens all the time. (This is Claude Code + MiniMax API, set up using official instructions) Basically, if I say get A, B and C done, it will only do A and B. I say, you still need to do C, so it does C but reverts the code for A. Things that Claude can usually one shot takes 5 iterations with MiniMax. I ended up switching to Claude to get one of my personal projects done.
- how_gauche 6mo agoI love it. It's not quite as good as Sonnet but it's quick, and Minimax 2.5 is like 1/4 the cost of Haiku. With enough of a harness around it, almost any breed of monkey can be coerced into producing excellent typewriter work. GLM 5 and 5.1 are other really competitive options on the price/performance curve
- stavros 6mo agoI haven't tried MiniMax but Claude has gotten seriously nerfed lately. A few weeks ago I could code all week on the $100/mo plan without getting close to the limit, now I consumed half the limit in the first day. Ridiculous, my company has committed to $200k annual plans and they changed the deal mid-way. We'll have to see about a refund.
- rcdwealth 6mo ago[dead]
- helix278 6mo ago> That is not a benchmark result. That is a different way of thinking about how AI models get built. tiresome
- mr_johnson123 6mo agoIt’s seems not to be completely open source.