MiMo
Xiaomi · Coding
Xiaomi MiMo is Xiaomi's open source reasoning model family, with a developer API priced per token, an OpenAI-compatible endpoint, and a free tier.
About MiMo
What Is Xiaomi MiMo
Xiaomi MiMo is Xiaomi's own family of large language models, built for reasoning, coding, and agent work. This agent AI model line started in April 2025 with the 7B MiMo AI model, which Xiaomi released under an open license, and it has grown into a lineup that today centers on the trillion-parameter MiMo-V2-Pro. The API lets you call these models from your own apps.
The main draw is that MiMo is both fast and open. You can run the weights yourself, or you can pay for hosted calls through Xiaomi's platform. The models also borrow the OpenAI and Anthropic API formats, so existing code often works with only a small change to the base URL and key.
The tradeoff is maturity. MiMo is a newer family than the big Western labs, and the top tier is aimed at agent pipelines rather than casual chat. Some advanced features, such as extended thinking modes in third-party tools, may lag behind what you get from older providers.
Getting Started
- Sign in to the Xiaomi MiMo platform at platform.xiaomimimo.com with a Xiaomi account.
- Open the console and create an API key. Copy it right away, because the key is shown only once.
- Set the base URL to https://api.xiaomimimo.com/v1 and paste your key into your app or SDK.
- Send a test request with an OpenAI or Anthropic compatible client, then pick the model you want to use.
Product Information
A quick look at MiMo's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- Developers building agent tools
- Coding assistants power users
- Budget-conscious teams
Tasks
- Writing and debugging code
- Long document and repo analysis
- Automating repeated workflows
Scenarios
- Shipping a feature with an AI that reads your repo
- Running a chatbot on a tight budget
- Self-hosting for privacy
Key features
Open Weights You Can Self-Host
Xiaomi releases MiMo weights under a permissive license, so you can download and run the models on your own machines instead of routing every request through a hosted service. That matters when you need to keep data in-house or want to fine-tune a model for a narrow task. You can pull the files from Hugging Face and ModelScope and serve them with common open-source runtimes.
OpenAI and Anthropic API Compatibility
The API follows two widely used request formats, which means most existing SDKs and tools connect with only a base URL and key change. If you already have code that calls OpenAI or Anthropic endpoints, pointing it at MiMo is often a few lines of work. That cuts the friction of trying a new provider without rewriting your app.
Long Context for Real Repositories
The current generation supports a context window that reaches 1M tokens, enough to hold a large codebase, a stack of documents, or a long conversation without chunking. The sliding-window attention design keeps memory use down as context grows, so long inputs stay practical rather than turning into a cost spike. For teams that work with big files, this is the feature that decides whether the model is usable at all.
Built for Tools and Agents
MiMo is tuned for tool calling and multi-step planning rather than one-shot answers. The models score well on public agent benchmarks, and Xiaomi has optimized them against real agent frameworks. In practice this means the model can plan a task, call the tools it needs, and carry the work through several steps before reporting back.
Fast and Cheap, Not Just Big
The lineup uses a mixture-of-experts design that activates a small slice of the network per request, which keeps speed high and cost low even at the larger tiers. A lightweight prediction layer generates several tokens at once, so responses stream out faster than a one-token-at-a-time model. For high-volume use, that gap shows up directly on the bill.
Multiple Models for Different Jobs
Xiaomi ships more than one model, from compact versions that fit modest hardware to the flagship for heavy agent work. You pick the tier that matches the task, so you are not paying flagship prices for simple calls. The family also extends to code-oriented tools and speech models for teams that want one vendor across several jobs.
Pros and cons
Pros
- Open weights let you self-host or fine-tune instead of renting everything.
- The API accepts OpenAI and Anthropic formats, so migration is quick.
- Long context up to 1M tokens suits large code and document tasks.
- Agent and tool-calling performance is a core design goal, not an afterthought.
- A free tier and low per-token pricing make early testing affordable.
Cons
- It is a younger family than the major Western models, so tooling and community answers are thinner.
- Some advanced options, such as extended thinking in third-party editors, may not work yet, which means you might need another provider for those cases.
- The best agent results assume a capable framework around the model, so raw chat alone shows less of its strength.
Frequently asked questions
MiMo is used for reasoning-heavy text work, coding, and agent tasks where a model plans and calls tools. It powers chatbots, coding helpers, and automation flows, and you reach it through the Xiaomi hosted API or by running the open weights yourself.
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