Can I run MiniMax M3 (MoE) locally?
MiniMax M3 (MoE) has 427.04 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 272.9 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2026-06-02. It's a mixture-of-experts model: all weights must fit in memory, but it generates faster than a dense model of the same size.
Memory needed by quantization
| Quant | Weights | Total needed (est.) |
|---|---|---|
| IQ1_S | 83.3 GB | 88.5 GB |
| IQ2_XXS | 110.0 GB | 116.6 GB |
| IQ2_M | 144.1 GB | 152.4 GB |
| Q2_K | 169.2 GB | 178.8 GB |
| IQ3_XXS | 163.3 GB | 172.6 GB |
| Q3_K_S | 194.8 GB | 205.7 GB |
| IQ3_M | 195.4 GB | 206.2 GB |
| Q3_K_M | 213.5 GB | 225.3 GB |
| IQ4_XS | 226.9 GB | 239.3 GB |
| Q4_0 | 240.2 GB | 253.3 GB |
| Q4_K_M | 258.9 GB | 272.9 GB |
| MXFP4 | 247.1 GB | 260.6 GB |
| Q5_K_M | 303.7 GB | 320.0 GB |
| Q6_K | 350.2 GB | 368.8 GB |
| Q8_0 | 453.7 GB | 477.5 GB |
| F16 | 854.1 GB | 897.9 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.50 GB | 0.27 GB | 0.14 GB |
| 8k | 1.01 GB | 0.53 GB | 0.28 GB |
| 16k | 2.01 GB | 1.07 GB | 0.57 GB |
| 32k | 4.03 GB | 2.14 GB | 1.13 GB |
| 64k | 8.05 GB | 4.28 GB | 2.26 GB |
| 128k | 16.11 GB | 8.56 GB | 4.53 GB |
From config.json: 60 KV-caching attention layers, 4 KV heads × 128 head dim. Max context 1024k. The tables above assume 4k context.
Which GPUs and Macs can run it?
✅ fits · ⚠️ fits with little headroom · ❌ doesn't fit on this one device (multiple GPUs or RAM offload may work; check your setup). Apple Silicon assumes macOS lets the GPU use ~67–75% of unified memory. All fit verdicts are estimates.
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