MiMo-V2.5
Overview
MiMo-V2.5 is an open-weight native omnimodal model from Xiaomi MiMo that entered public beta on April 23, 2026. It combines a 310-billion-parameter sparse Mixture-of-Experts (MoE) language backbone with dedicated vision and audio encoders to understand text, images, video, and audio in long-context agent workflows.
Key Features
- Native Omnimodal Understanding: Processes text, image, video, and audio input in one model, using a 729M-parameter vision encoder and a 261M-parameter audio encoder in addition to the language backbone.
- 310B Sparse MoE Architecture: Uses 310 billion total parameters, 15 billion active parameters, 256 routed experts, and eight selected experts per token.
- Efficient 1M-Token Context: Interleaves 39 Sliding Window Attention layers with nine global-attention layers in a 5:1 pattern. Xiaomi reports nearly 6x lower KV-cache storage while retaining long-context performance.
- Multimodal and Coding Evaluation: Xiaomi reports 77.9 on MMMU-Pro, 87.7 on Video-MME, 23.8 on Claw-Eval Multimodal, 65.8 on Terminal-Bench 2.0, and 56.1 on SWE-Bench Pro.
- Agent-Oriented API Controls: Supports deep thinking, streaming, function calling, structured output, and Xiaomi's separately billed web-search service.
Best Use Cases
- Multimodal Analysis: Understanding screenshots, charts, scanned documents, video, and audio alongside written instructions and contextual data.
- Visual and Media-Aware Agents: Agents that must inspect multimodal evidence, reason about it, call tools, and produce a text response or action plan.
- General Coding and Automation: Software tasks that benefit from image-based UI context, terminal tools, structured output, and lower API cost than the Pro variant.
- Long-Context Applications: Document analysis, codebase assistance, media archives, and extended conversations that need up to a one-million-token context.
Capabilities and Limitations
| Capability | Description |
|---|---|
| Reasoning | Deep thinking is enabled by default and can be turned off with thinking.type. Xiaomi's official multimodal results include 77.9 on MMMU-Pro and 81.0 on CharXiv RQ. |
| Coding | Xiaomi reports 71.8 on MiMo Coding Bench, 62.3 on Claw-Eval Text, 65.8 on Terminal-Bench 2.0, and 56.1 on SWE-Bench Pro. |
| Creative Writing | Supports general and long-form text generation. |
| Multimodal | Accepts text, image, video, and audio input and produces text output. Official results include 87.7 on Video-MME, 83.5 on DailyOmni, and 23.8 on Claw-Eval Multimodal. |
| Context Window | 1M tokens. |
| Max Output | 128K tokens. |
| Tool Use | Supports function calling, structured output, streaming, and Xiaomi's web-search tool. In thinking-mode agent conversations, tool-call history must retain the complete reasoning_content field. |
| Multilingual | The official model repository identifies English and Chinese support. |
Known Limitations
- The hosted API provides multimodal understanding with text output; it does not generate images, audio, or video as native response modalities.
- In thinking mode, custom
temperatureandtop_pvalues are ignored; the API forces1.0and0.95. Multi-turn tool workflows that omit historicalreasoning_contentcan fail with HTTP 400 or lose context quality.
Standard Pricing
The token prices below are shown in USD per 1 million tokens; web search is billed in USD per use.
| Model | Input (USD / 1M Tokens) | Cache Write (USD / 1M Tokens) | Cache Read (USD / 1M Tokens) | Output (USD / 1M Tokens) | Web Search (USD / use) |
|---|---|---|---|---|---|
| MiMo-V2.5 | $0.14 | $0.14 | $0.0028 | $0.28 | - |
Credits settlement: B.AI converts charges at 1 USD = 1,000,000 Credits and deducts Credits from the account balance.
Prices shown in the documentation are B.AI standard reference prices for base billing purposes. B.AI may provide lower actual usage costs through account benefits. Specific prices and account benefits are subject to the platform display and final billing records.