MiMo-V2.5-Pro
MiMo-V2.5-Pro is an open-weights language model from Xiaomi, released April 22, 2026. It has 1T parameters (mixture-of-experts, 30B active). The context window is 1M tokens. API price: $0.43 input / $0.87 output per million tokens.
Today, we are releasing and open-sourcing MiMo-V2.5-Pro. It is our most capable model to date, delivering significant improvements over its predecessor, MiMo-V2-Pro, in general agentic capabilities, complex software engineering, and long-horizon tasks.
Check it against your own PC →
Can you run MiMo-V2.5-Pro locally?
Even with 32 GB of VRAM and 32 GB of RAM it is too large to run at a usable speed on a single consumer GPU. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.
| GPU memory | Verdict | Best quant | VRAM | RAM | tok/s |
|---|---|---|---|---|---|
| 6 GB VRAM | Too large | – | – | – | – |
| 8 GB VRAM | Too large | – | – | – | – |
| 12 GB VRAM | Too large | – | – | – | – |
| 16 GB VRAM | Too large | – | – | – | – |
| 24 GB VRAM | Too large | – | – | – | – |
| 32 GB VRAM | Too large | – | – | – | – |
Ready-made quantizations on Hugging Face: unsloth/MiMo-V2.5-Pro-GGUF · bartowski/MiMo-V2.5-Pro-GGUF · DevQuasar/XiaomiMiMo.MiMo-V2.5-Pro-GGUF · AesSedai/MiMo-V2.5-Pro-GGUF · gghfez/MiMo-V2.5-Pro-ik_llama-unfused-GGUF · ji-farthing/MiMo-V2.5-Pro-DFlash-draft-ik-llama-GGUF
Benchmark results
Epoch AI has not published results for MiMo-V2.5-Pro yet. New models are usually evaluated within days to weeks.
Links
Announcement · Hugging Face: XiaomiMiMo/MiMo-V2.5-Pro
More from Xiaomi
MiMo V2.6 Flash MOPD · MiMo V2.6 Pro MOPD · MiMo-V2.6-Pro · MiMo-V2.6-Flash · MiMo V2.6 Pro RL · MiMo V2.6 Flash RL · MiMo-V2.5 · MiMo-V2-Pro