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MiniMax M2.5 released: 80.2% in SWE-bench Verified
- mythz 8mo agoReally looked forward to this release as MiniMax M2.1 is currently my most used model thanks to it being fast, cheap and excellent at tool calling. Whilst I still use Antigravity + Claude for development, I reach for MiniMax first in my AI workflows, GLM for code tasks and Kimi K2.5 when deep English analysis is needed. Not self-hosting yet, but I prefer using Chinese OSS models for AI workflows because of the potential to self-host in future if needed. Also using it to power my openclaw assistant since IMO it has the best balance of speed, quality and cost: > It costs just $1 to run the model continuously for an hour at 100 tokens/sec. At 50 tokens/sec, the cost drops to $0.30.
- user2722 8mo ago!!!!!! Incredibly cheap!!!!! I'll have to look for it in OpenRouter.
- amunozo 8mo agoFor the moment is free in Opencode, if you want ot try it.
- algo_trader 8mo ago> MiniMax first in my AI workflows, GLM for code tasks and Kimi K2.5 Its good to have these models to keep the frontier labs honest! Can i ask if you use the API or a monthly plan? Do the monthly plan throttle/reset ? edit: i agree that MM2.1 most economic, and K2.5 generally the strongest
- mythz 8mo agoUsing a coding plan, haven't noticed any throttling and very happy with the performance. They publish the quotas for each of their plans on their website [1]: - $10/mo: 100 prompts / 5 hours - $20/mo: 300 prompts / 5 hours - $50/mo: 1000 prompts / 5 hours [1] https://platform.minimax.io/docs/guides/pricing-coding-plan https://platform.minimax.io/docs/guides/pricing-coding-plan
- miroljub 8mo agoThey count one prompt as 15 requests. That gives you exactly 1500 API requests for 5 hours. Tokens are not counted.
- jhack 8mo agoAnd it's available on their coding plans, even the cheapest one.
- turnsout 8mo agoWith the GLM news yesterday and now this, I'd love to try out one of these models, but I'm pretty tied to my Claude Code workflow. I see there's a workaround for GLM, but how are people utilizing MiniMax, especially for coding?
- claythearc 8mo agoanything with an open ai compatible endpoint can have claude code router put in front of it afaik https://github.com/musistudio/claude-code-router https://github.com/musistudio/claude-code-router
- amunozo 8mo agoI use Opencode, when the model is free for the moment. I have not used Claude Code so I cannot compare.
- hasperdi 8mo agoyou can use Claude Code with these models. You just need to pass the right env vars. Have a look at the client setup guide on z.ai
- turnsout 8mo agoInteresting—thanks!
- 3adawi 8mo agoWish my company allowed more of these LLMs through Github Copilot, stuck with OpenAi, Anthropic and Google LLMs where they burn my credit one week into the month
- denysvitali 8mo agoBtw, the model is free on OpenCode for now
- logicprog 8mo agoHm. The benchmarks look too good to be true and a lot of the things they say about the way they train this model sound interesting, but it's hard to say how actually novel they are. Generally, I sort of calibrate how much salt I take benchmarks with based on the objective properties of the model and my past experiences with models from the same lab. For instance, I'm inclined to generally believe Kimi K2.5's benchmarks, because I've found that their models tend to be extremely good qualitatively and feel actually well-rounded and intelligent instead of brittle and bench-maxed. I'm inclined to give GLM 5 some benefit of the doubt, because while I think their past benchmarks have overstated their models' capabilities, I've also found their models relatively competent, and they 2X'd the size of their models, as well as introduced a new architecture and raised the number of active parameters, which makes me feel like there is a possibility they could actually meet the benchmarks they are claiming. Meanwhile, I've never found MiniMax remotely competent. It's always been extremely brittle, tended to screw up edits and misformat even simple JavaScript code, get into error loops, and quickly get context rot. And it's also simply just too small, in my opinion, to see the kind of performance they are claiming.
- Bolwin 8mo agoThat feels like a problem with your harness. What are you using it with?
- OsrsNeedsf2P 8mo ago> M2.5-Lightning [...] costs $0.3 per million input tokens and $2.4 per million output tokens. M2.5 [...] costs half that. Both model versions support caching. Based on output price, the cost of M2.5 is one-tenth to one-twentieth that of Opus, Gemini 3 Pro, and GPT-5. Huge - if not groundbreaking - if the benchmark stats are true.
- therealmarv 8mo agoyes it's good. But you should also look at GLM 5 and Kimi K2.5 when looking at M2.5. It's amazing we have so many good and cheap open weight models now which are really not far behind the top models from the big US AI companies. Anthropic Claude Code and OpenAI Codex plans are subsidised. The Chinese open weight models hosted in US or Europe make more sense to use when you want to stay model agnostic and less dependent on a single AI company with relative expensive APIs.
- lm28469 8mo agoCost per token doesn't really matter anymore, cost per task it more important.
- sinuhe69 8mo agoI hope better and cheaper models will be widely available because competition is good for the business. However, I'm more cautious about benchmark claims. MiniMax 2.1 is decent, but one can really not call it smart. The more critical issue is that MiniMax 2 and 2.1 have the strong tendency to reward hacking, often write nonsensical test report while the tests actually failed. And sometimes it changed the existing code base to make its new code "pass", when it actually should fix its own code instead. Artificial Analysis put MiniMax 2.1 Coding index on 33, far behind frontier models and I feel it's about right. [1] [1] https://artificialanalysis.ai/models/minimax-m2-1 https://artificialanalysis.ai/models/minimax-m2-1
- osti 8mo agoThat's what I found with some of these LLM models as well. For example I still like to test those models with algorithm problems, and sometimes when they can't actually solve the problem, they will start to hardcode the test cases into the algorithm itself.. Even DeepSeek was doing this at some point, and some of the most recent ones still do this.
- edoceo 8mo agoSounds exactly what a junior-dev would do without proper guidance. Could better direction in the prompts help? I find I frequently have to tell it where to put what fixes. IME they make a lot of spaghetti (LLMs and juniors)
- heliumtera 8mo ago[flagged]
- throawayonthe 8mo agowtf kinda juniors are you interacting with
- edoceo 8mo agoLots of self-taught; looking for an entry level.
- simonw 8mo agoPelican is recognizable but not great, bicycle frame is missing a bar: https://gist.github.com/simonw/61b7953f29a0b7fee1f232f6d9826b42?permalink_comment_id=5984793#gistcomment-5984793 https://gist.github.com/simonw/61b7953f29a0b7fee1f232f6d9826...
- UltraSane 8mo agoYou should switch to an octopus riding a bike, much harder.
- mentalgear 8mo agoalso much less in training data by now
- onlyrealcuzzo 8mo agoNot an SVG, but I'm pretty impressed by what Gemini 3.0 Fast does: https://gemini.google.com/share/52c1229bd1d9 https://gemini.google.com/share/52c1229bd1d9 /imagine an svg of an octopus riding a bike. 1 arm shading its eyes from the sun, another waving a cute white flag, 2 driving the bike, 2 peddling the wheels, and 2 drifting behind in the wind
- amluto 8mo agoI think part of the point is that the SVG is the hard part. Gemini is quite good at generating images, but it’s trained to generate raster images.
- deleted 8mo ago[deleted]
- miohtama 8mo agoMaybe in the future models render a bitmap and trace the vector image with a tool, like a human would do.
- jbotz 8mo agoHmm, I am not sure the missing front fork is worse than the unsteerable front wheel mountings (which look like rear wheel mountings) most models so far have produced. It might be better... sort of an admission of an unsolved problem in design of the bike rather than producing something that looks approximately correct but can't possibly work. Like a "TODO" comment in code. Also the position of the pelican on the bike would be somewhat awkward, but fits anatomically with a pelican's relatively short legs. In fact I can remember riding (or trying to ride) an adult bike as a young child using a similar position.
- thedangler 8mo agoWouldn't it be nice if we have language specific llms that work on average computers. Like LLM that only trained on Python 3+, certain frameworks, certain code repos. Then you can use a different model for searching the internet to implement different things to cut down on costs. Maybe I have no idea what I'm talking about lol
- theLiminator 8mo agoI imagine some sort of distill like this would be possible, but I think multi-language training really helps the LLM.
- rbren 8mo agoA reasonably sized OSS model that's this good at coding is a HUGE step forward. We've done some vibe checks on it with OpenHands and it indeed performs roughly as good as Sonnet 4.5. OSS models are catching up
- aliljet 8mo agoI wonder if these are starting to get reasonable enough to use locally?
- mchusma 8mo agoThis is cool, but they mentioned affordability, and said this is about $1/hour to run, which is about what I pay for claude code on $200/mo plan. This is not literally true, sometimes I'm running up to 3 concurrent intermittently throughout the day for maybe 60 hours per week. So I do believe if there is something that comes up that is literally continuous, would be interesting, but I'm not sure about it right now. I would be curious if anyone has anything they would literally use running 24/7.
- motbus3 8mo agoEveryone is using this sort of let me group the plots weirdly instead of sorting them to make harder to compare. I see you folks
- jbellis 8mo agoM2 was one of the most benchmaxxed models we've seen. Huge gap between SWE-B results and tasks it hasn't been trained on. We'll put 2.5 on the list. https://brokk.ai/power-ranking https://brokk.ai/power-ranking
- tgrowazay 8mo ago$1/hr sounds suspiciously close to a price of one A100 80GB GPU. Maybe an 8x node assuming batching >= 8 users per node.
- hsaliak 8mo agoIt's interesting that we do not have a wave of tier-2 companies with NNN Million dollar cap releasing anything competitive. It's the big 4 labs vs the chinese labs. No Tier-2.
- vessenes 8mo agoThere’s mistral
- dcre 8mo agoNot a serious test, but I tried M2.5 briefly in OpenCode on a very simple task equivalent to the last commit or two here[0] and it was really, really bad. This is a 250 line self-contained standalone script and what it does is very simple. M2.5 would have required far more detailed prompting to get me the result Opus 4.6 can do with the vaguest hints. [0]: https://github.com/oxidecomputer/console/pull/3070/commits https://github.com/oxidecomputer/console/pull/3070/commits
- pseudony 8mo agoI have built a relatively complete process supervisor in Go - cross-platform, http management API, separate actor-like goroutines for each process and the main supervisor. All using Minimax m2.1 on open code. Sure, it needs steering, but I have actually preferred it to claude which is much too eager
- liyuan851277048 8mo ago[dead]
- liyuan851277048 8mo ago[dead]
- XCSme 8mo agoIt's benchmaxxed: https://aibenchy.com/model/minimax-minimax-m2-5-medium/ https://aibenchy.com/model/minimax-minimax-m2-5-medium/