Overview
MiMo-V2.5-Pro is Xiaomi's (XiaomiMiMo) flagship open-weight language model, built as a Mixture-of-Experts (MoE) network with about 1023.2B total parameters and roughly 42B active per token.
- License: Mit
- Context length: 1M tokens
- Languages: en, zh
- Minimum hardware: ~572 GB VRAM
- Strengths: reasoning, coding and on-device inference
Highlights
- Trillion-scale MoE — ~1023.2B total with roughly 42B active per token.
- Agentic tool use — native tool calling drives long task chains coherently.
- Software engineering — strong code generation and editing on repo-level tasks.
- 1M context — a 1,048,576-token window for large codebases and long documents.
What it is good at
MiMo-V2.5-Pro was trained for long, multi-step work rather than one-shot chat. Its capability tags point to a few clear strengths.
- Agentic tool use — with native tool_calling, it can drive long task chains spanning many tool calls while staying coherent across the run.
- Software engineering — strong code generation and editing, the area Xiaomi positioned it for alongside complex repo-level tasks.
- Long-context reasoning — the thinking and reasoning capabilities pair with the 1M-token window to work over large codebases or long document sets in one pass. It handles English and Chinese.
Running it locally
This is a large model. At 1023.2B total parameters the full weights need a multi-GPU server (80GB-class cards such as H100, or several RTX 4090s) to hold the model and a meaningful slice of the 1,048,576-token context; quantized builds lower that bar but still demand serious memory. Pull the weights from Hugging Face:
huggingface-cli download XiaomiMiMo/MiMo-V2.5-Pro
From there you can serve it with vLLM or SGLang, load it through Transformers, or open it in Atomic Chat with one click once the weights are on disk.
License
MiMo-V2.5-Pro is released under the MIT license. You can use, modify, redistribute, and build commercial products on it, as long as the copyright and license notice travel with the code.