Xiaomi releases MiMo v2.6 with two model sizes
Xiaomi's latest language model arrives with transparent training practices and competitive benchmarks, sparking discussion about the cost and speed advantages of Chinese AI development.
What to know
- Xiaomi released MiMo v2.6 in two sizes (Flash: 15B activated params, Pro: 42B activated params) with detailed benchmarks and transparent training documentation.
- The release is being compared to major U.S. models (GPT-6 Astra, Claude variants) and praised for cost efficiency and accessibility.
- Community discussion centers on whether Chinese AI development's lower cost and speed undercut the competitive position of U.S. companies.
- Some commenters question benchmark credibility, while others highlight the quality of Xiaomi's real-time training dashboard and technical transparency.
The dispute Whether MiMo v2.6's benchmark performance claims are reliable, with some commenters skeptical of certain comparisons while acknowledging transparency as a strength. · positions read across 58 posts and comments
Xiaomi's transparency and cost efficiency represent genuine competitive advantages worth adopting or shifting to.
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“I really like how transparent they've been about the training of this model. The realtime dashboard they shared during training was an incredible learning and teaching tool for me…”
rao-v · Hacker News ↗
Benchmark comparisons are unreliable and some results should be treated with skepticism.
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“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.”
user43928 · Hacker News ↗
Chinese model competitiveness explains U.S. AI lab calls for development slowdowns and competitive margin pressure.
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“maybe this is why Dario want to slow down AI development and all the big AI labs in the USA is singing the same song…they are afraid of Chinese good enough LLM model killing their margin.”
MangoCoffee · Hacker News ↗
Xiaomi Model developer and publisherrao-v Hacker News commenteruser43928 Hacker News commenterlwansbrough Hacker News commenter
How it unfolded 4 developments, newest first · click a bar or a number to jump articlespostscomments
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Debate emerges over benchmark credibility and geopolitics
Commenters express skepticism about certain benchmark results while acknowledging the quality of Xiaomi's release strategy. Some speculate about motivations behind U.S. AI labs' calls for development slowdowns, linking them to competitive concerns about Chinese models.
“maybe this is why Dario want to slow down AI development and all the big AI labs in the USA is singing the same song…they are afraid of Chinese good enough LLM model killing their margin.”
— MangoCoffee -
Xiaomi MiMo-V2.6 from @XiaomiMiMo is live on OpenRouter. Three new models. A 1T+ parameter flagship, an open-source MoE, and a ~10x faster variant of the flagship. All three take text, image, video, and audio with 1M context. More in the thread 🧵
2 more of the top 3 · 51 posts in this stretch
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I have done the same. I hesitated for way too long. I shouldn’t have.I get way more usage for way less money without any quality or performance degradation. My $200 Codex Pro plan allowance is depleted in 2-3 days. Sometimes Tibo announces a usage reset. But GPT-5.6 models are really not good for coding. Sol has been making increasingly more…
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MiMo-V2.6-Pro: Neues Modell führt Open-Weight-Ranking an Xiaomis MiMo-V2.6-Pro setzt sich in Benchmarks an die Spitze der Open-Weight-Modelle und ist zudem günstiger als ähnlich leistungsfähige offene Konkurrenz. https://www. heise.de/news/MiMo-V2-6-Pro-Ne…
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Community highlights cost and affordability advantages
Users comment on the competitive advantage of Chinese models over American alternatives, particularly regarding pricing and resource efficiency. The discussion focuses on practical applications and the thinning competitive moat.
“Anyone else more excited about Chinese models than American models these days? Big thing for me is affordability.”
— lwansbrough -
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…
1 more of the top 2 · 2 posts in this stretch
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Anyone else more excited about Chinese models than American models these days? Big thing for me is affordability.
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Technical community evaluates benchmarks and transparency
Commenters on Hacker News analyze MiMo v2.6's performance across Terminal Bench 4.0 and ExploitGym benchmarks, comparing it to GPT-6 Astra, Claude Fable 5.1, and other models. Reviewers praise Xiaomi's transparency in sharing training data and methodologies.
“I really like how transparent they've been about the training of this model. The realtime dashboard they shared during training was an incredible learning and teaching tool for me…”
— 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…
2 more of the top 3 · 5 posts in this stretch
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Flash[1]: 309B total / 15B activated parametersPro [2]:, 1.02T total / 42B activated parameters[1]:
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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).
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Xiaomi releases MiMo v2.6
Xiaomi announced MiMo v2.6, available in two model configurations. The Flash version has 309B total parameters with 15B activated, while the Pro version has 1.02T total parameters with 42B activated.
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2 outlets first by HN Best, 4d ago · also HN Frontpage · read ↗
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Also covered reported alongside — the timeline has no entry for these yet
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first by VentureBeat, 4d ago · also TestingCatalog AI News, RuntimeWire, Xiaomi, Latent Space
4 more headlines
- Xiaomi open-sources MiMo-V2.6 Pro and Flash models TestingCatalog AI News · 4d ago
- Xiaomi open-sources MiMo-V2.6 and the RL machinery behind it RuntimeWire · 4d ago
- Xiaomi debuts open-weight omnimodal models MiMo-V2.6 Pro and Flash; Pro allegedly performs “on par with Opus 5 and GPT-5.6 Sol across most agent benchmarks” Xiaomi · 4d ago
- [AINews] Xiaomi MiMo-V2.6-Pro 1T-A42B: the new top Open Weights model, trained for $3M Latent Space · 4d ago
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first by Artificial Analysis, 4d ago · also HN Frontpage
1 more headline
- MiMo-v2.6-Pro: Intelligence, Performance and Price Analysis HN Frontpage · 4d ago
and 1 smaller piece
What people are saying 19 voices from 3 sites · best of 58 · verbatim
- Sep 22
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Welcome to the dark side. I've been on Kimi, with a little DeepSeek-V4-Pro, GLM 5.2/5.3, and MiMo thrown in, for probably about a year now. It's great here!For DeepSeek, I recommend their Reasonix harness strongly, due to its alignment to DeepSeek's prefix cache. It means mostly (95%+) cache hit input tokens, so very cheap large-scale code…
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It is an impressive model. Agreed on most that is written on this page, with the exception of it being fast. I ran it on my own LLM benchmark suite[1] and it is faster than DeepSeek but still much slower than leading models. But it's pricing is where it really shines.KillSwitch-Bench 1.0 Claude Opus 5 66.9 GPT-6 Astra 57.9 Claude Fable 5.1 46.7…
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It feels suspicious that MiMo-V2.6 Pro gets 46 in de index while DeepSeek-V4.1 (https://artificialanalysis.ai/models/deepseek-v4-1-flash) gets 39. According to the appendix at the bottom of https://mimo.xiaomi.com/mimo-v2-6 the deepseek model sometimes surpasses mimo and it's not so far behind in capabilities. A week ago opus 5 appeared 1 points…
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is there a good metric of model degredation over time?Im a bit lazy and only use the free models different companies host and the biggest difference i see is that some models (Gemini, OpenAI) get progressively stupid in long chats. You end up having to start a new session every oncr in a while. Or they get really hung up on a theme and cant shift…
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Granted this is an awesome release and I loved watching the livestreamed RL dashboard, I found this message on the dashboard (https://mimo.xiaomi.com/rl/) quite funny:> we also removed the cyber dataset from the upcoming pro run, since we observed some bad patterns in the rollout logs.And this in the model card (emphasis mine):> Aligned RL: Cold…
- Sep 21
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I was absolutely mind blown when I saw how they were publishing that training dashboard while US models publish 100s of pages of reports (just provide a "copy as MD" button, folks, in the future). I was thinking about doing something similar but did not know how to show it, and this is a perfect example for someone who wants to show whatever they…
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Here's an image->html test for it using 2.6 Pro Ultraspeed, along with comparisons for grok 4.7 and Astra.Design: https://image.non.io/78795662-8bfc-4e14-8d72-3738392aa6b3.we...MiMo 2.6 Pro Ultraspeed (36min): https://html.non.io/annui-mimo/Grok 4.7 (25min): https://html.non.io/Annui-grok/Astra (19min): https://html.non.io/annui/Overall this felt…
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Are people using MiMo models as their daily drivers in a company setting? If so, how? I know they're available over OpenCode and directly from Xiaomi, but those are not great options. OpenCode Go straight up doesn't give any guarantees about training on your data, and Xiaomi says that they won't but it's unclear.With some models you can find…
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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…
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Xiaomi just dropped Mimo 2.6 Pro which claims to be the best open source model. I played with it, and was pretty impressed: - Insanely cheap: With some standard assumptions, its 15x cheaper than Kimi K3, 6x cheaper than GLM 5.3 and 2x cheaper than DeepSeek V4 and only 2x more expensive than DeepSe...
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MiMo-V2.6-Pro debuts as the top open weights model on the Artificial Analysis Intelligence Index (46). At $0.13 per Intelligence Index task, it lands on the Intelligence vs. Cost per Task Pareto frontier @Xiaomi has just released MiMo-V2.6-Pro, an open weights model with major advances in intellig...
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Xiaomi is contributing a LOT to open research with this release. All of their training run details are basically out there in the open — reward plots, hyperparameters, data mixtures, even costs. They also release a subset of their RL envs and a smaller model for people to play around with on mor...
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How?!! Xiaomi has just released their new OPEN SOURCE model MiMo-V2.6-Pro: - multimodal text/image/audio/video - score ~ same as GPT-5.6-Sol Max - 9x cheaper input tokens - 23x cheaper output tokens 💀 Also about 20x cheaper than Opus 5... and the weights are already on Hugging Face. Hard to se...
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Alert: Xiaomi just open-sourced MiMo-V2.6. Two natively omnimodal models, Pro and Flash, under MIT license 🔥. Pro scores 46.32 on the Artificial Analysis Intelligence Index, the highest of any open model to date. weights:
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“We're open-sourcing Pro and Flash, MiMo-V2.6-Distill-Qwen-9B, the technical report, 7K+ RL task environments, an end-to-end RL framework and composable mini-harnesses.” wow 🔥
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Real open model nerds knew Xiaomi is cooking with MiMo! An open RL dashboard for the top scoring open model is aura. [image] [embedded post]
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Xiaomi MiMo v2.6 Pro is the best open weight model in the world, almost on par with GPT 5.6 Sol (max)!
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> got lots of clever behind the scene tricks like Google or Deepseek writeups) and benchmark scoresXiaomi MiMo is led by Luo Fuli, a former Alibaba & DeepSeek employee. Perhaps it is due to Luo just how similar Xiaomi's tech & GTM approach is to DeepSeek's.- How Luo Fuli Keeps an Earthy Touch as she Soars Through the AI World…
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Xiaomi MiMo v2.6: https:// mimo.xiaomi.com/mimo-v2-6 Discussion: http:// news.ycombinator.com/item?id=4 9792730