MiMo-V2.5-Pro
Overview
MiMo-V2.5-Pro is an open-weight text model from Xiaomi MiMo that entered public beta on April 23, 2026. The higher-capacity member of the MiMo-V2.5 family uses a 1.02-trillion-parameter sparse Mixture-of-Experts (MoE) architecture with 42 billion active parameters and is designed for long-horizon agents, software engineering, and complex reasoning.
Key Features
- 1.02T Sparse MoE Architecture: Uses 1.02 trillion total parameters, 42 billion active parameters, 384 routed experts, and eight selected experts per token.
- Hybrid Long-Context Attention: Interleaves 60 Sliding Window Attention layers with 10 global-attention layers and a 128-token sliding window. Xiaomi reports that the 6:1 local-to-global pattern reduces KV-cache storage by nearly 7x.
- 1M Context and 128K Output: Supports a one-million-token context window and up to 128K output tokens for repository-scale work, long documents, and extended agent trajectories.
- Agent and Coding Evaluation: Xiaomi reports 1,581 Elo on GDPVal-AA, 63.8 on ClawEval, 57.2 on SWE-Bench Pro, 78.9 on SWE-Bench Verified, and 68.4 on Terminal-Bench 2.0.
- Controllable Reasoning and Tools: Deep thinking is enabled by default but can be disabled. The API supports streaming, function calling, and structured output.
Best Use Cases
- Long-Horizon Software Engineering: Repository navigation, multi-file implementation, debugging, testing, and tool-driven work that must remain coherent across long trajectories.
- Complex Agent Workflows: Tasks involving repeated function calls, planning, execution, and correction over large working contexts.
- Long-Document Reasoning: Analysis and synthesis across extensive code, technical documents, research material, or conversation history.
- Self-Hosted Model Development: Commercial inference, fine-tuning, or secondary training where MIT-licensed weights and framework-level deployment control are required.
Capabilities and Limitations
| Capability | Description |
|---|---|
| Reasoning | Deep thinking is enabled by default and can be turned off with thinking.type. Xiaomi reports 48.0 on Humanity's Last Exam with tools and 34.0 without tools. |
| Coding | Xiaomi reports 57.2 on SWE-Bench Pro, 78.9 on SWE-Bench Verified, 68.4 on Terminal-Bench 2.0, and an implementation rank of 3.4 on FrontierSWE. |
| Creative Writing | Supports general and long-form text generation. |
| Multimodal | Text input and text output. |
| 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. Xiaomi reports 83.6 on GlobalMMLU, 91.5 on C-Eval, and 90.2 on CMMLU for the Pro Base model, but does not publish a complete language-support list. |
Known Limitations
mimo-v2.5-prois a text model and does not provide the full-modal understanding available inmimo-v2.5.- 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-Pro | $0.435 | $0.435 | $0.0036 | $0.87 | - |
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.