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Xiaomi MiMo v2.6

Xiaomi MiMo v2.6

volf_

Comments (158)

  • rao-v
    I know we have strong views on what a truly open model is (open weights, open training data, open training code etc.) but I really like how transparent they’ve been about the training of this model.The realtime dashboard they shared during training (https://mimo.xiaomi.com/rl/) was an incredible learning and teaching tool for me, and they’ve been unusually comprehensive in sharing details about their methodology (check out that tech report - it's got lots of clever behind the scene tricks like Google or Deepseek writeups) and benchmark scores (even the stuff they didn’t do well on).If you’re releasing an open model going forward, please consider offering the community more of this transparency!
  • lwansbrough
    Anyone else more excited about Chinese models than American models these days? Big thing for me is affordability.
  • simonw
  • stymaar
    Flash[1]: 309B total / 15B activated parametersPro [2]:, 1.02T total / 42B activated parameters[1]: https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Flash-RL[2]: https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Pro-RL
  • nemothekid
    Looking at the frontend design examples; why do these models seem to love the "01 - UPPERCASE TEXT" motif. It's everywhere now (see https://try.cloudflare.com/, which has '01 · QUICK TUNNELS', but no "02" anywhere).
  • user43928
    I don't trust any of the benchmarks where Opus 5 surpasses Astra or Fable 5.1.Maybe Terminal Bench 4.0 and ExploitGym are reasonable.Terminal Bench 4.0 GPT 6 Astra 59.6 Claude Fable 5.1 55.1 Claude Opus 5 49.0 MiMo-V2.6-Pro 34.9 MiMo-V2.6-Flash 28.8 DeepSeek V4.1 Flash 26.8 MiMo-V2.5-Pro 1.5 ExploitGym GPT 6 Astra 42.4 Claude Fable 5.1 30.4 Claude Opus 5 22.1 MiMo-V2.6-Pro 17.8 MiMo-V2.6-Flash 6.0 MiMo-V2.5-Pro 0.1 DeepSWE v1.1 DeepSeek V4.1 Flash 74.2 Claude Opus 5 74.0 GPT 6 Astra 74.0 MiMo-V2.6-Pro 71.9 Claude Fable 5 70.0 MiMo-V2.6-Flash 67.9 MiMo-V2.5-Pro 19.0
  • GodelNumbering
    Mimo has been one of those models that I have been rooting for since the first I used it, the 2.5 pro which I have used quite a bit, was very concise, very aware of how much context needs to be read for which tasks and would always keep the context tight. Also surprisingly good at strategic thinking. I had published a comparison between it and Terra where Terra was found to be using much more avg context for similar tasks https://dirac.run/posts/gpt-5-6-vs-mimo-2-5-pro-context-bloa...Interesting but not surprising trend across the board seems to be, the flash models seems to have caught up with the pro-sized models of H1'26. No surprise all labs are rushing to bigger models.EDIT: Wow, took a detailed look at the benchmarks. Mimo 2.6 pro, the 1T model leads Kimi K3, a 2.8T param model in 14 out of 15 benchmarks (and the last one is near tie)!! Good to see they also kept the price the same, and landed in the greenest quardrant of the intelligence vs speed of AA.
  • vatsachak
    Wow, the chinese labs are getting good at advertising model releases. The moat is thin.Some features of the release I like:- Demonstration of diverse tasks, such as using a DAW- Graphs from various benchmarks and price ranges- Real world use of the model in scientific environments
  • toephu2
    I said this years ago, LLMs are a commodity (or were becoming one at the time). They are dime a dozen. Even the frontier ones. OpenAI and Anthropic have no moat.No moat and competition is good for consumers though.
  • volf_
    I've got a working recipe to run this model on Dual DGX Spark: https://github.com/volfco/spark-vllm-docker/blob/main/recipe...Averages ~25-35tok/s which isn't bad for a first attempt.
  • thrownawaysz
    >Night 0.8x Usage, 00:00-08:00 -UTC+8It's because offpeak electricity is cheaper?Funnily it's perfect if you are in the Pacific Time Zone because you can use it daytime 9am to 5pm
  • pulkitsh1234
    Anyone knows what they used to create the videos ? Is the model driving a program like Davinci Resolve / After Effects ? or is the model writing code to then generate these videos via some library.
  • syntaxing
    All these new models are such tease for us folks with 128GB of shared memory. Buying another unit now to expand to 256GB is a mortgage payment but it’s getting tempting…
  • drob518
    Conspicuous that there’s no reference to GLM 5.3/Flash in the reported benchmarks. Just Deepseek and Kimi.
  • anon
    undefined
  • ddxv
    This looks great in terms of cost and capabilities, truly pushing the frontier forward in terms of open weight light weight models.
  • eriquesito
    Funny that all but one video has audio, the house 3D model one, where you can hear (what I assume are) Xiaomi's engineers talking about who knows what.
  • MisterMunchkin
    I really liked MiMo 2.5, it was really affordable and actually had vision, unlike DeepSeek. (DeepSeek has only recently added it)Just tried 2.6 flash on a really niche topic I specialise in and it has done a really good job. They’ve definitely polluted their training data with claudeslop, but looking past the slop there is a decent model.
  • DanMcInerney
    This is a big week. Probably getting next OpenAI and Anthro models, Grok 4.7, Mimo, etc. These open source model releases are why I can't take the "slow down" crowd seriously. I pitted older Mimo, qwen, step, gpt-oss, and other models against each other playing games like Werewolf and Sketch.io-like games where I let them talk shit while they played against each other. Mimo was by far pareto frontier of game-playing for the models that were <$0.15/m input tokens on OpenRouter. Qwen was pareto frontier in the shit talking game though. Qwen's hilarious. https://www.tiktok.com/@clankerfights/video/7642862917582425...
  • esafak
    It tops the intelligence vs cost Pareto frontier and, uniquely for a Chinese model, does well in response time too.https://artificialanalysis.ai/models/mimo-v2-6-pro#intellige...That's pretty fast; I think I'll try it: https://openrouter.ai/xiaomi/mimo-v2.6-flash
  • algoth1
    Finally a lab that doesn't cheat on the charts
  • alfalfasprout
    The moat for OAI and anthropic seems to be very quickly shrinking. Chinese labs are now using RSI-like approaches and even without resorting to heavy distillation they're catching up in a couple of months vs. what would have been 6-12 months a year prior.And as these models get better the pace of training is quickly speeding up too.This doesn't bode particularly well for anthropic/OAI after they go public.
  • bertili
    They mixed up DeepSeek 4.1 Flash with something else on this page, possibly DeepSeek 4.1 Flash means Gemini 3.8 Flash.
  • varispeed
    These benchmark are useless as they don't say whether they were done before or after Fable and Astra got nerfed.
  • gigatexal
    Leaning into what it cost to train is hilarious and an obvious shot at US frontier labs spending tens to hundreds of millions or more to train their models.
  • NooneAtAll3
    does anyone know what unnamed model is on paretto frontier picture right between MiMo 2.5 and 2.6?so weird to acknowledge someone being on the front edge, but not name it
  • spwa4
    As for the stats that everyone wants:MiMo-V2.6-Flash-310B-A15B roughly GPT-5.6 Luna / Claude 4.9 according to benchmarks MiMo-V2.6-Pro-1.02T-A42B roughly GPT-5.6 Sol / Opus 5 according to benchmarksPerhaps with IQ2 flash will run on 128G M5?
  • 16t96
    [flagged]
  • nlcs
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  • nofpu
    [dead]
  • unpopularopp
    [flagged]
  • omani
    ah, would you look at that. I was wondering why mimo 2.5 became "dumber" the last weeks. I was speculating they are probably about to release a new version of the model. because the model really acted out a lot. especially the last two weeks. dont know, was just a feeling, highly speculative.but now I got my "proof".
  • jwpapi
    In the chart they use "Pareto Line", which I think is wrong. Pareto is 20% effort leading to 80% results. Which could be interpreted as models costing 20% having 80% of peak intelligence, but that’s not what it looks like to me.It looks like the "Frontier Line" to me, which is also often misinterpreted. frontier does not mean the best models. It means all models that are not strictly dominated, meaning in most cases: Not same price or cheaper and more intelligent.I personally would like the word frontier to be used with more criterias: Open Weights, per use-case, etc etc. This would make model selection easier, but I understand it’s not an easy thing to do.