Everything about MiMo-V2.5-Pro

Overview

MiMo-V2.5-Pro is a language model from Xiaomi (MiMo), released on April 22, 2026. That makes it 6 months old as of October 22, 2026. Its weights are published: you can download it and run it on your own servers, or use one of the 24 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).

Pricing and budget

MiMo-V2.5-Pro costs $0.44 per million input tokens and $0.87 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 $0.01; a thousand of those tasks, $10.44.

That is in line with open-weight models, whose median output price is $1.

Tokens read back from cache cost $0.004 per million, which helps an agent that keeps resending the same context.

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

Benchmark results

As of October 22, 2026, Epoch AI publishes no score for MiMo-V2.5-Pro on our basket's benchmarks. To place it, rely on its specifications and price, then test it on your own cases.

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. Its knowledge stops at December 2024: beyond that, it needs web search or your documents.

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

The weights are published on Hugging Face (XiaomiMiMo/MiMo-V2.5-Pro). See also our list of open-source models.

What is it good for?

Given its category, MiMo-V2.5-Pro 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.

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

Alternatives

In the same category, the models closest to MiMo-V2.5-Pro are:

• MiMo-V2.6-Pro (Xiaomi (MiMo), $0.87 per million output tokens)
• Trinity Large Thinking (Arcee AI, $0.80 per million output tokens)
• Llama-3.3-70B-Instruct (Meta, $0.76 per million output tokens)
• Qwen3.6 35B-A3B (Alibaba Cloud (Qwen), index 55.3)