Can I run Mistral Small 3.1 24B locally?
Mistral Small 3.1 24B has 24.01 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 16.6 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2025-03-11. This is an older model; see the current list for newer options.
Memory needed by quantization
| Quant | Weights | Total needed (est.) |
|---|---|---|
| IQ1_S | 4.7 GB | 6.2 GB |
| IQ2_XXS | 6.2 GB | 7.8 GB |
| IQ2_M | 8.1 GB | 9.8 GB |
| Q2_K | 9.5 GB | 11.3 GB |
| IQ3_XXS | 9.2 GB | 10.9 GB |
| Q3_K_S | 11.0 GB | 12.8 GB |
| IQ3_M | 11.0 GB | 12.8 GB |
| Q3_K_M | 12.0 GB | 13.9 GB |
| IQ4_XS | 12.8 GB | 14.7 GB |
| Q4_0 | 13.5 GB | 15.5 GB |
| Q4_K_M | 14.6 GB | 16.6 GB |
| MXFP4 | 13.9 GB | 15.9 GB |
| Q5_K_M | 17.1 GB | 19.2 GB |
| Q6_K | 19.7 GB | 21.9 GB |
| Q8_0 | 25.5 GB | 28.1 GB |
| F16 | 48.0 GB | 51.7 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.67 GB | 0.36 GB | 0.19 GB |
| 8k | 1.34 GB | 0.71 GB | 0.38 GB |
| 16k | 2.68 GB | 1.43 GB | 0.75 GB |
| 32k | 5.37 GB | 2.85 GB | 1.51 GB |
| 64k | 10.74 GB | 5.70 GB | 3.02 GB |
| 128k | 21.47 GB | 11.41 GB | 6.04 GB |
From config.json: 40 KV-caching attention layers, 8 KV heads × 128 head dim. Max context 128k. 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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