How much VRAM does MiMo-V2.5 310B (MoE) need at Q4_K_M? Xiaomi 1M SWA model
MiMo-V2.5 310B at Q4_K_M is a 244 GB resident deployment for 1M context, or about 62 GB with active-expert offload.
MiMo-V2.5 310B at Q4_K_M with native 1M context needs about 244 GB of VRAM with all experts resident. The smaller sibling of MiMo-V2.5-Pro activates 15B parameters per token from a 310B total pool. Active-expert offload drops the resident footprint to roughly 62 GB. Sliding-window attention with a 128-token window keeps the key-value cache under 49 GB at the full 1M context.
By TechCompare · Updated
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Estimated VRAM required
244 GB
310B params at Q4_K_M, 1,048,576 token context, batch 1, inference.
Estimate accuracy: Weights within ~2%. KV cache within ~5% for standard GQA models, ~10% for MLA (DeepSeek). Real VRAM may vary with framework (vLLM vs llama.cpp vs Transformers), Flash Attention, and driver overhead.
Sliding-window attention applied: This model caps 4 of every 5 layers at a 128-token window. KV cache estimate is 81% smaller than naive full-attention math at this context length.
Hardware that fits
How this is calculated
The 310B parameter pool requires 174 GB of weights at Q4_K_M. The 48-layer architecture uses group-query attention with variable KV heads: 8 in the 9 full-attention layers, 4 in the 39 sliding-window layers. The QK and V dims share the same asymmetry as the Pro variant, so the effective head_dim is 160. Sliding-window attention caps 39 of 48 layers at a 128-token window. The key-value cache at the full 1M context uses about 48 GB. Activation and software overhead adds about 22 GB. In active-only mode the resident weights shrink to 8 GB, which drops total usage to 62 GB.
Verdict
Resident mode fits on four 80GB datacenter cards or two 141GB H200 cards. Active-only at 62 GB fits on a single 80GB card or a 96GB unified memory workstation. This is the practical option if you want the MiMo architecture on hand: the Pro variant needs 2.8x the VRAM for 2.8x the active parameters.
More MiMo scenarios
Frequently asked questions
What's the difference between MiMo-V2.5 and MiMo-V2.5-Pro?
Does MiMo-V2.5 fit on a single GPU?
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