All models › xiaomi
MiMo-V2.5-Pro
xiaomi · MIT license · on Arena since 28 Apr 2026
Download
Arena score1465#37 of 416 in Chat, paid models included
Size1023.2 B43.8 B active per token (mixture of experts)
4-bit download620 GBweights only, Q4_K_M
Max context1024Ktokens, from the model config
Where to use it for free
- Download and run it at home: official weights · GGUF files for Ollama and LM Studio
Arena scores
Rank among all models, paid ones included. Source: Arena leaderboard dataset.
Speed on popular hardware
| Hardware | GPU memory | Fits? | Speed |
|---|---|---|---|
| RTX 3060 12 GB | 12 GB | Does not fit | — |
| RTX 4060 Ti 16 GB | 16 GB | Does not fit | — |
| RTX 3090 | 24 GB | Does not fit | — |
| RTX 4090 | 24 GB | Does not fit | — |
| RTX 5090 | 32 GB | Does not fit | — |
| RX 7900 XTX | 24 GB | Does not fit | — |
| 2 × RTX 3090 | 48 GB | Does not fit | — |
| 4 × RTX 3090 | 96 GB | Does not fit | — |
| Mac M4 Max 128 GB | 96 GB | Does not fit | — |
| Ryzen AI Max+ 395 128 GB | 96 GB | Does not fit | — |
| 8 × H100 SXM | 640 GB | Fits in GPU | 68 tok/s |
Estimate at 4-bit with 32K context, 64 GB of DDR5 for offload. Speed ≈ memory bandwidth × 70% ÷ data read per token; real numbers vary by about ±30%.
GPU memory needed
| Level | 8K context | 32K context | 128K context | Quality vs full |
|---|---|---|---|---|
| Q3_K_M | 513 GB | 514 GB | 520 GB | +4.7% noticeable loss |
| Q4_K_M | 621 GB | 623 GB | 629 GB | +1.2% very small loss |
| Q5_K_M | 729 GB | 730 GB | 736 GB | +0.4% near-lossless |
| Q6_K | 840 GB | 842 GB | 848 GB | +0.2% near-lossless |
| Q8_0 | 1088 GB | 1090 GB | 1096 GB | ≈ 0% same as full |
| F16 | 2048 GB | 2049 GB | 2055 GB | ≈ 0% same as full |
Weights + context cache (from the model's architecture) + runtime. Quality: increase in perplexity against the full model, from llama.cpp tests, scaled by model size. Simulate your own setup.
Chat score over time
145015001550
MayJunJulAugSeptOct
MiMo-V2.5-Pro 1465Best paid model
Arena score from 17 Apr 2026 to 15 Oct 2026.
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