# Xiaomi livestreams MiMo-V2.6's RL run — a public training dashboard

> Xiaomi put the reward curves of a frontier-scale RL run on a public web page while the run is still going.

- Org: Xiaomi
- Date: 2026-09-17
- Category: resource, showcase
- Source: https://mimo.xiaomi.com/rl/
- Canonical page: https://ai-tldr.dev/releases/xiaomi-mimo-v2-6-rl-livestream/

## In short

Xiaomi opened a live dashboard for the reinforcement-learning run behind MiMo-V2.6, streaming per-step metrics as they happen. Each step uses 1,568 prompts with 16 rollouts each, roughly 2 billion tokens.

## What it is

A live dashboard at mimo.xiaomi.com/rl now streams the reinforcement-learning post-training of MiMo-V2.6 as it happens. Fuli Luo, who leads Xiaomi's MiMo team, announced it on 17 September 2026 after what he described as nearly half a year of silence spent on one question: how far reinforcement learning actually scales. The model itself is not released — the training run is what is on display.

## How it works

Every step of the run pulls 1,568 prompts, samples 16 rollouts from each, and works through roughly 2 billion generated tokens. Code, general, visual, cybersecurity and chat-agent tasks are trained together in a single multi-harness setup rather than one specialist run per domain, and rewards combine test-case checks with rubric grading under what the team calls agentic in-group credit assignment. The dashboard exposes task composition, context length and time per step live.

## Why it matters

Anyone trying to scale reinforcement learning is working mostly from published post-mortems, where the failed variants have been edited out. Watching a real run tick over gives researchers a reference for what healthy curves and step costs look like at this size. The recipe is not open yet, so the dashboard is a window rather than a manual — but it is a far more honest one than a results table.

## Who it's for

RL researchers, post-training engineers, people tracking Chinese labs

## Try it

https://mimo.xiaomi.com/rl/

## Quick facts

- Maker: Xiaomi MiMo team
- Model: MiMo-V2.6 — still mid-training
- Dashboard: mimo.xiaomi.com/rl
- Per step: 1,568 prompts x 16 rollouts, about 2B tokens
- Task mix: Code, general, visual, cybersecurity and chat agents
- Announced by: Fuli Luo, MiMo team lead
- Open source: Not yet — details promised over the coming weeks

## FAQ

### Can you see MiMo-V2.6's benchmark scores on the dashboard?

The MiMo-V2.6 dashboard streams metrics from the run in progress — task composition, context length and per-step timing — rather than a finished scorecard. Xiaomi had not published final model benchmarks or specifications when the livestream opened, because the reinforcement-learning phase is still going. What you are watching is the curve, not the result.

### Is Xiaomi open-sourcing the MiMo-V2.6 RL recipe?

Not as one drop. Fuli Luo said the MiMo team will open-source the details piece by piece over the coming weeks instead of publishing a single comprehensive report. So the methodology behind the run is not available yet; the live dashboard is the only public window into it at the moment.

### How big is each training step?

Each step of the MiMo-V2.6 run draws 1,568 prompts and generates 16 rollouts per prompt, which works out to roughly 2 billion tokens of generated text per step. Several task families — code, general reasoning, visual, cybersecurity and chat agents — are trained together in one multi-harness run rather than in separate specialist stages.

### Why is a public training dashboard unusual?

Labs almost never show a run while it is happening. Reward curves and eval metrics mid-training reveal how well a recipe is working, which is competitively sensitive, so they normally appear only in a report after the fact. Xiaomi's MiMo-V2.6 livestream inverts that, and the Hacker News thread on it drew 494 points and 139 comments in under a day.

## Links

- [Live Dashboard](https://mimo.xiaomi.com/rl/)
- [HN Discussion](https://news.ycombinator.com/item?id=49732270)
- [Announcement Recap](https://www.explainx.ai/blog/xiaomi-mimo-v2-6-rl-scaling-livestream-2026)
- [MiMo on GitHub](https://github.com/XiaomiMiMo/MiMo)