# MiMo-V2.6 — Xiaomi's trillion-parameter model ships under MIT

> Xiaomi released MiMo-V2.6 with open MIT weights, a 1M-token context, and cybersecurity scores far above its own V2.5 line.

- Org: Xiaomi
- Date: 2026-09-21
- Category: model
- Source: https://mimo.xiaomi.com/mimo-v2-6
- Canonical page: https://ai-tldr.dev/releases/xiaomi-mimo-v2-6/

## In short

MiMo-V2.6 is Xiaomi's new model series: a 1.02T-parameter Pro, a cheaper Flash, and a 20x-faster UltraSpeed variant. Weights for Pro and Flash are on Hugging Face under the MIT license with a 1M-token context.

## What it is

Three new models join Xiaomi's MiMo line as MiMo-V2.6: a trillion-parameter Pro built for long-horizon and cybersecurity work, a cheaper full-modality Flash, and an UltraSpeed build of Pro that Xiaomi says runs up to 20x faster for latency-sensitive jobs. Weights for MiMo-V2.6-Pro-RL, MiMo-V2.6-Flash-RL, and MiMo-V2.6-Distill-Qwen-9B are published on Hugging Face under the MIT license.

## How it works

The Pro model is a sparse mixture of experts: 1.02 trillion total parameters with 42 billion active per token, 384 routed experts of which 8 fire per token, and a 1M-token context. Xiaomi credits the jump to scaled reinforcement learning — fully asynchronous GRPO over batches of 1,568 prompts by 16 rollouts per step, plus groupwise agentic grading and multi-prefix multi-teacher on-policy distillation. A 681M-parameter MiMo ViT reads images and a 308M AudioTokenizer handles sound.

## Why it matters

An MIT license on a trillion-parameter omni-modal model is unusual — teams can self-host, fine-tune, and ship MiMo-V2.6 commercially with no usage restrictions. On Xiaomi's own table Pro reaches 89.9% on Terminal Bench 2.1, above Claude Opus 5 at 89.1%, and 94.0% on CyberGym against 40.0% for MiMo-V2.5 Pro. Xiaomi recommends serving it with SGLang or vLLM.

## Who it's for

teams self-hosting open-weight frontier models

## Try it

Pull XiaomiMiMo/MiMo-V2.6-Pro-RL from Hugging Face and serve it with SGLang or vLLM.

## Quick facts

- Maker: Xiaomi
- Parameters (Pro): 1.02T total, 42B active
- Context window: 1M tokens
- License: MIT
- Variants: Pro, Flash, Pro-UltraSpeed, Distill-Qwen-9B
- Weights: Hugging Face (XiaomiMiMo)
- Serving: SGLang or vLLM

## FAQ

### Is MiMo-V2.6 open source?

The weights are. Xiaomi publishes MiMo-V2.6-Pro-RL, MiMo-V2.6-Flash-RL, and MiMo-V2.6-Distill-Qwen-9B on Hugging Face under the MIT license, which places no restriction on commercial use or modification. The hosted API variants — mimo-v2.6-pro, mimo-v2.6-flash, and mimo-v2.6-pro-ultraspeed — are served by Xiaomi separately through its own platform.

### What hardware do you need to run MiMo-V2.6 Pro?

MiMo-V2.6-Pro-RL is a 1.02 trillion parameter mixture of experts with 42 billion parameters active per token, so it needs a multi-GPU node rather than a single card. Xiaomi recommends deploying it with SGLang or vLLM using specific tensor-parallel configurations. The 9B Distill-Qwen build exists for people who cannot host the full model.

### How does MiMo-V2.6 compare to MiMo-V2.5?

The gap is large on agentic work. On Xiaomi's published table MiMo-V2.6 Pro scores 71.9% on DeepSWE v1.1 against 19.0% for MiMo-V2.5 Pro, 76.9% against 49.1% on Toolathlon-Verified, 89.9% against 65.2% on Terminal Bench 2.1, and 94.0% against 40.0% on CyberGym.

### What is MiMo-V2.6-Pro-UltraSpeed for?

MiMo-V2.6-Pro-UltraSpeed is Xiaomi's latency build: the company describes it as flagship V2.6-Pro performance running up to 20x faster, aimed at real-time and latency-sensitive workloads. Pick it when response time matters more than cost per token. The plain mimo-v2.6-flash variant is the cheaper option for high-frequency calls at large scale.

## Links

- [MiMo V2.6 Launch Page](https://mimo.xiaomi.com/mimo-v2-6)
- [MiMo-V2.6-Pro-RL Weights](https://huggingface.co/XiaomiMiMo/MiMo-V2.6-Pro-RL)
- [MiMo-V2.6 Collection](https://huggingface.co/collections/XiaomiMiMo/mimo-v26)
- [API Model Updates](https://mimo.mi.com/docs/en-US/updates/model)