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Xiaomi MiMo v2.6

148 pointsby 57m agomimo.xiaomi.com
47 comments
47m agoHN ↗

Finally a lab that doesn't cheat on the charts

44m agoHN ↗

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

40m agoHN ↗

I've never used worst smartphones than anything from Xiaomi, bloated ad infested borderline malware territory fork of Android. Maybe just me but whenever I see them on HN I just can't think anything good about this company.

38m agoHN ↗

It's a big company, like Microsoft or Google. Some of their products are good and some are bad.

18m agoHN ↗

ironic to this thread, I have less bloatware and ads since I switched from Verzion to Pixel on Fi (many years ago)

Curious if Verizon / ATT still force apps on your phone, eg. NFL and Amazon apps, Fi service is subpar

22m agoHN ↗

It's funny, I have the exact opposite reaction. This is probably misguided on my part, but Xiaomi is one of the very few major tech companies that I don't have an immediate strong negative reaction to. Everything I've bought from them, from robot vacuum to mobile phone, has been reasonably well designed, didn't break, and was priced fairly. I also think their car looks badass.

I'm sure they're doing all kinds of terrible things, like all major companies. I just can't help but like them. Also, this model looks great, and I'll give their subscription a shot next month.

22m agoHN ↗

I still have a xiaomi mi 11 lite, my wife has a 15t. The cameras are the best for the price. The way they chove ads down your throat at every opportunity should be illegal though

40m agoHN ↗

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...

40m agoHN ↗

This looks great in terms of cost and capabilities, truly pushing the frontier forward in terms of open weight light weight models.

40m agoHN ↗

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".

30m agoHN ↗

I guess that would only be possible if your provider was Xiaomi itself?

21m agoHN ↗

yes. I use opencode and opencode uses Xiaomi as a provider.

39m agoHN ↗

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).

28m agoHN ↗

My guess is that by function they break down frontend sections or components into pieces and I believe document things for themselves on some level, or purposely are verbose in this way. It is probably also shaped by users and existing web patterns. They probably get reinforced by models the more common they become.

37m agoHN ↗

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!

23m agoHN ↗

curious why the HF pill (on the right) always has inaccurate values

14m agoHN ↗

Those this mean they've fine-tuned this Qwen 3.5 9B on output from the V2.6 model?

10m agoHN ↗

It is a 9B agentic model developed by Xiaomi MiMo through supervised fine-tuning of Qwen3.5-9B on MiMo-generated data

32m agoHN ↗

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…

29m agoHN ↗

Is there a gamechanger around the corner to reduce DRAM requirements?

21m agoHN ↗

this is to offload VRAM to DRAM (for GP comment), and makes no difference for URAM

15m agoHN ↗

unified memory, not sure if anyone uses URAM, I human hallucinated it

9m agoHN ↗

You could always stream from SSD storage. Especially effective if you get a cheap old-gen HEDT with lots of PCIe slots to add NVMe storage to and reasonable overall PCIe bandwidth.

27m agoHN ↗

They mixed up DeepSeek 4.1 Flash with something else on this page, possibly DeepSeek 4.1 Flash means Gemini 3.8 Flash.

26m agoHN ↗

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

24m agoHN ↗

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 benchmarks

Perhaps with IQ2 flash will run on 128G M5?

22m agoHN ↗

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.

14m agoHN ↗

It's an honest, load-bearing, simple thing.-

15m agoHN ↗

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.

8m agoHN ↗

There are two (or more) concepts named after the same person:

- Pareto efficiency/Pareto curves: Basically the convex hull of points along the edge of a graph, indicating the best tradeoff between the axes. This is what the post is talking about.

- Pareto principle: this is the 80/20 rule you're talking about

14m agoHN ↗

Anyone else more excited about Chinese models than American models these days? Big thing for me is affordability.

11m agoHN ↗

No, because I'd rather not support our economic and military rivals.

10m agoHN ↗

Agreed, and also because I support freedom of speech!

9m agoHN ↗

I'm Canadian so this sentiment has little value in 2026 unfortunately.

13m agoHN ↗

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
11m agoHN ↗

Maybe you should not trust any of the benchmarks!