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MiMo-V2-Flash (Non-Thinking)

xiaomi · MIT license · on Arena since 16 Oct 2026

Download
Arena score1330#119 of 144 in Coding, paid models included
Size309.8 B16.5 B active per token (mixture of experts)
4-bit download188 GBweights only, Q4_K_M
Max context256Ktokens, from the model config

Where to use it for free

Arena scores

ArenaScoreRankVotes
Coding1330#119 of 1446K

Rank among all models, paid ones included. Source: Arena leaderboard dataset.

Speed on popular hardware

HardwareGPU memoryFits?Speed
RTX 3060 12 GB12 GBDoes not fit—
RTX 4060 Ti 16 GB16 GBDoes not fit—
RTX 309024 GBDoes not fit—
RTX 409024 GBDoes not fit—
RTX 509032 GBDoes not fit—
RX 7900 XTX24 GBDoes not fit—
2 × RTX 309048 GBDoes not fit—
4 × RTX 309096 GBDoes not fit—
Mac M4 Max 128 GB96 GBDoes not fit—
Ryzen AI Max+ 395 128 GB96 GBDoes not fit—
8 × H100 SXM640 GBFits in GPU177 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

Level8K context32K context128K contextQuality vs full
Q3_K_M156 GB156 GB159 GB+4.7% noticeable loss
Q4_K_M189 GB189 GB192 GB+1.2% very small loss
Q5_K_M221 GB222 GB225 GB+0.4% near-lossless
Q6_K255 GB256 GB258 GB+0.2% near-lossless
Q8_0330 GB331 GB333 GB≈ 0% same as full
F16620 GB621 GB624 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.

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