Technical specifications of Xiaomi MiMo-V2-Pro
| Item | Xiaomi MiMo-V2-Pro |
|---|---|
| Provider | Xiaomi |
| Model ID | mimo-v2-pro |
| Model family | MiMo-V2 |
| Model type | Agentic foundation model / reasoning model |
| Primary input | Text |
| Primary output | Text |
| Context window | Up to 1,000,000 tokens |
| Total parameters | Over 1 trillion |
| Active parameters | 42 billion |
| Architecture | Hybrid-attention MoE |
| Release window | March 2026 |
| Benchmark signal | Artificial Analysis Intelligence Index: #8 globally; PinchBench: #3 globally |
What is Xiaomi MiMo-V2-Pro?
Xiaomi MiMo-V2-Pro is Xiaomi’s flagship MiMo model for real-world agentic work. Xiaomi describes it as the model behind agent systems that orchestrate complex workflows, handle production engineering tasks, and keep operating reliably across long, multi-step jobs.
Main features of Xiaomi MiMo-V2-Pro
- Agent-first design: built for workflows, tool use, and task execution rather than only chat-style answers.
- Ultra-long context: supports up to 1 million tokens, which makes it practical for huge codebases, long documents, and extended task traces.
- Large MoE scale: more than 1T total parameters with 42B active parameters, paired with hybrid attention for efficiency.
- Strong coding ability: Xiaomi says its coding performance surpasses Claude 4.6 Sonnet in internal evaluations.
- Reliable tool calling: Xiaomi highlights improved tool-call stability and accuracy for agent scaffolds.
- Framework-friendly: Xiaomi says the model is being paired with agent frameworks such as OpenClaw, OpenCode, KiloCode, Blackbox, and Cline.
Benchmark performance of Xiaomi MiMo-V2-Pro
Xiaomi’s March 2026 materials place MiMo-V2-Pro at #8 worldwide on the Artificial Analysis Intelligence Index and #3 globally on PinchBench average task completion rate. Xiaomi also reports a ClawEval score of 61.5, which it describes as close to Claude Opus 4.6 and ahead of GPT-5.2 on that benchmark.
Xiaomi MiMo-V2-Pro vs MiMo-V2-Flash vs MiMo-V2-Omni
| Model | Best for | Key difference |
|---|---|---|
| MiMo-V2-Flash | Fast, efficient text reasoning | Smaller MoE model tuned for efficiency; 309B total / 15B active parameters |
| MiMo-V2-Pro | Deep agentic reasoning and long workflows | Flagship text agent model with 1M-token context and 1T+ parameters |
| MiMo-V2-Omni | Multimodal understanding + execution | Unifies text, vision, and speech for multimodal agent tasks |
When to use Xiaomi MiMo-V2-Pro
Use MiMo-V2-Pro when you need long-context reasoning, multi-step agent orchestration, code-heavy workflows, or production-style task execution. It is the better fit than MiMo-V2-Flash when depth matters more than speed, and the better fit than MiMo-V2-Omni when your workload is text-first instead of multimodal.
Limitations
MiMo-V2-Pro is positioned as a text-first agent model, so native multimodal work is better handled by MiMo-V2-Omni. As with any benchmark-led model, real results will still depend on prompt design, tool quality, and how the agent is wired into your stack.