Xiaomi Mimo 2.6 live post-training dashboard

wolttam

Hah, it would be great to see more labs pick this up.

krm01

This is pretty neat. What would be a good reason for the other Model providers to not do this?

speedgoose

I didn't know 2 thirds of the training data would be source code.

thehamkercat

This is crazy, but sadly anthropic/openai will never do this, what has happened to this world, where chinese companies are more open than US or even EU companies

rozab

Why are they doing this? To try head off accusations about distillation?

liuliu

When you run benchmarks while training, isn't that the definition of contamination? Asking because I am not sure if this is normal in big labs now.

ProfessorLayton

2.6 Pro: >started 2026-09-15 10:32 UTC For some reason I thought training took much, much longer than what the progress bar suggests. This is really neat, I'm currently using mimo 2.5 pro, and it's decent (or great given the price). Hopefully their next one is multimodal.

joelwallis

I been using MiMo-V2.5 to do most of my work as software engineer, on a variety of projects I'm working on, and I been VERY happy with ROI. The model is very powerful! Not perfect – I've run in hallucination loops once or twice, but nothing a stop-then-continue wouldn't solve. The cost is unbelievably low, and the quality of intelligence I get is equivalent to when I was working mostly with Anthropic models (late last year/early this year). I'm fully invested in MiMo and I'm very happy with it. -- PS: I also check almost daily to see if other models are capable of doing such great work. And they do – DS4F is powerful and DS41 is impressive, GLM 5.3 Flash gets a job done well, etc. – but when I add cost of M-token in the ROI math, Jeez! MiMo is an order of magnitude better.

levocardia

You'd think they would make it less obvious that they are running their whole operation with Claude

impulser_

The Chinese labs are just making fun of the US labs at this point. Where is the cool shit from the US labs?

esafak

That's the kind of transparency we need! That DeepSWE benchmark puts it in frontier territory: https://artificialanalysis.ai/agents/coding-agents?coding-ag...

fzysingularity

Very cool to see the openness here, and likely more like this will come from smaller startups where they win users on transparency.

dr_dshiv

Well, if open source AI is dangerous (for OpenAI/Anthropic IPOs?), this is like watching a time bomb.

passive

Neat! I've been trying out their next model for the last week, which I assume is a version of this, and it's been a good experience so far. I had used 2.5-pro for a hefty chunk of development, and found it to work like a somewhat forgetful senior engineer who was new to my project. Very capable, would almost always choose a reasonable option, if not always the best one for the project, and not great at multi-tasking. Generally, made me comfortable not scrutinizing the code line-by-line, but still needed a bit of steering once projects got to a reasonable size. The next model is a clear step up in the multi-tasking capability at least, with me very rarely having to steer the implementation of a well-defined issue. In terms of code, I found MiMo-V.2.5-pro to be extremely conservative, implementing minimal solutions. The next model seems a little bit more ambitious, in positive ways, making good guesses about gaps/next steps. It also seems to be a fair bit better at design, at least for the little bit I've done, it was good at translating my concepts to practical elements on screen, and cleaned things up nicely as I made suggestions.

ricardobeat

For reference, Mimo-v2.5-Pro scored 19% on DeepSWE 1.1. This is looking great. Fable scores 70%, Kimi K3 69%, Astra 74% (all on max effort). https://deepswe.datacurve.ai/blog/deepswe-v1-1

ernsheong

Mino 2.5 has been my workhorse for coder and tester agents (the ones planner agents delegate tasks to)

dude250711

Distillation in real-time? Very interesting!

dr_kiszonka

Very curious that everyone here (so far) seems to assume this dashboard presents real data.

ttul

$5 per second if my eyes don’t fool me. That’s ~$432K per day. Enough to rent 3,000 B300 nodes on Modal.

rao-v

I absolutely love that someone is doing this! Why isn’t IBM for Granite or Google for Gemini? If you are going to develop a near frontier model, and you don’t think you have special sauce up your sleeve, why not making training runs and RL environment scores etc. visible to the world? I’m genuinely learning quite a bit just from the dashboard