Can I run Mistral Small 4 119B (2603) (MoE) locally?
Mistral Small 4 119B (2603) (MoE) has 119.40 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 76.7 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2026-01-23. 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 | 23.3 GB | 25.1 GB |
| IQ2_XXS | 30.7 GB | 33.0 GB |
| IQ2_M | 40.3 GB | 43.0 GB |
| Q2_K | 47.3 GB | 50.4 GB |
| IQ3_XXS | 45.7 GB | 48.6 GB |
| Q3_K_S | 54.5 GB | 57.9 GB |
| IQ3_M | 54.6 GB | 58.1 GB |
| Q3_K_M | 59.7 GB | 63.4 GB |
| IQ4_XS | 63.4 GB | 67.3 GB |
| Q4_0 | 67.2 GB | 71.2 GB |
| Q4_K_M | 72.4 GB | 76.7 GB |
| MXFP4 | 69.1 GB | 73.3 GB |
| Q5_K_M | 84.9 GB | 89.9 GB |
| Q6_K | 97.9 GB | 103.5 GB |
| Q8_0 | 126.9 GB | 133.9 GB |
| F16 | 238.8 GB | 251.4 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.09 GB | 0.05 GB | 0.03 GB |
| 8k | 0.19 GB | 0.10 GB | 0.05 GB |
| 16k | 0.38 GB | 0.20 GB | 0.11 GB |
| 32k | 0.75 GB | 0.40 GB | 0.21 GB |
| 64k | 1.51 GB | 0.80 GB | 0.42 GB |
| 128k | 3.02 GB | 1.60 GB | 0.85 GB |
From config.json: 36 KV-caching attention layers (MLA, 320-dim compressed cache). 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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