Xiaomi MiMo-V2.5-Pro Review: The Open-Source Model That Cracked Arena Top 6

Xiaomi MiMo-V2.5-Pro Review: The Open-Source Model That Cracked Arena Top 6

On April 23, 2026, Xiaomi released the MiMo-V2.5 series of full-modal large models. A month later, the model’s Arena performance confirms Xiaomi’s investment in large models has entered the first tier.

Arena Performance

  • Arena text leaderboard: global sixth (~1489 range), highest among open-source models
  • Agent index: open-source #1, top five across all models globally
  • Global open-source comprehensive intelligence index: tied #1

These results mean MiMo-V2.5-Pro’s real-user conversation performance has surpassed GPT-5.5 (Arena text seventh) and most closed-source models.

Core Capabilities

Agent capability. Agent index #1 among open-source indicates significant advantages in tool calling, multi-step task planning, and autonomous execution — aligned with Xiaomi’s IoT ecosystem experience.

Million-level long context. Supports 100K+ token context window, practical for codebase analysis, legal document review, and long video subtitle understanding. At equivalent benchmark scores, MiMo-V2.5-Pro’s token usage efficiency is relatively lower.

Full-modal coverage. The series covers text, speech (V2.5-TTS), and more — one of the few open-source model families covering multiple modalities.

Ecosystem Compatibility

Xiaomi announced MiMo-V2.5 series is compatible with nearly all Chinese inference chips — an important usability indicator for domestic enterprise users. The model can be deployed without relying on NVIDIA GPUs.

Comparison

DimensionMiMo-V2.5-ProQwen3.6-35B-A3BGLM-5.1
Arena TextGlobal #6 / OS #1Not Top 10Not Top 10
CodeModerateNear Claude 4.5Arena Code #5
Long ContextMillion+Million+Unclear
Multi-modalText + SpeechText-focusedText-focused

Recommendations

  • IoT / Smart Home: MiMo-V2.5-Pro’s Agent capability and Xiaomi ecosystem integration.
  • Chinese chip deployment: Broad compatibility reduces hardware dependency.
  • Long document processing: Million-token context + efficient token usage.

Main sources: