MiMo-V2.6-Flash: pricing, context and performance

What you need to know

MiMo-V2.6-Flash is a language model from Xiaomi (MiMo), released on September 22, 2026. It is a very recent release. Its weights are published: you can download it and run it on your own servers, or use one of the 27 API providers that list it on models.dev. It has a reasoning mode: it can "think" before answering, which helps with multi-step problems but uses more tokens, and therefore more money.

We file it under open-weight models (68 models in this category on the site).

Measured performance

As of October 22, 2026, Epoch AI publishes no score for MiMo-V2.6-Flash on our basket's benchmarks. To place it, rely on its specifications and price, then test it on your own cases.

Pricing and budget

MiMo-V2.6-Flash costs $0.14 per million input tokens and $0.28 per million output tokens (developer's price, checked on October 22, 2026).

To put it in perspective: reading 20,000 tokens (about thirty pages) and writing 2,000 costs roughly $0.003; a thousand of those tasks, $3.36.

That is 3.6 times cheaper than the median output price of open-weight models ($1).

Tokens read back from cache cost $0.003 per million, which helps an agent that keeps resending the same context.

To estimate your own budget, use the agent cost calculator.

Context and capabilities

Its context window reaches 1,048,576 tokens, roughly 1,573 pages of text at 500 words per page: enough to load a whole book or a mid-sized codebase. A single answer can run to 131,072 tokens.

It accepts as input: text, image, audio and video.

It can call tools (functions, APIs) and return structured JSON output, which makes it a possible foundation for an AI agent.

The weights are published on Hugging Face (XiaomiMiMo/MiMo-V2.6-Flash-RL). See also our list of open-source models.

What is it good for?

Given its category, MiMo-V2.6-Flash is mainly aimed at projects where you want control over your data or hosting, or want to adapt the model to your field.

Its very large context window makes it worth considering for analysing large sets of documents in a single request.

Its very low cost (under half a cent for our sample task) means it can be called thousands of times a day.

Before adopting it, test it on your own examples: benchmarks measure standard tasks, not your job.

What could replace it?

In the same category, the models closest to MiMo-V2.6-Flash are:

• DeepSeek V4 Flash 0731 (DeepSeek, index 68.2)
• MiMo-V2.5 (Xiaomi (MiMo), $0.28 per million output tokens)
• Granite 4.2 8B (IBM (Granite), $0.25 per million output tokens)
• Gemma 4 26B A4B IT (Google DeepMind, $0.34 per million output tokens)