Can I run Kimi K3 (MoE) locally?
Kimi K3 (MoE) has 2779.93 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 1770.6 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2026-06-13. 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 | 542.1 GB | 570.2 GB |
| IQ2_XXS | 715.8 GB | 752.7 GB |
| IQ2_M | 938.2 GB | 986.2 GB |
| Q2_K | 1101.5 GB | 1157.7 GB |
| IQ3_XXS | 1063.3 GB | 1117.5 GB |
| Q3_K_S | 1268.3 GB | 1332.8 GB |
| IQ3_M | 1271.8 GB | 1336.4 GB |
| Q3_K_M | 1390.0 GB | 1460.5 GB |
| IQ4_XS | 1476.8 GB | 1551.7 GB |
| Q4_0 | 1563.7 GB | 1642.9 GB |
| Q4_K_M | 1685.3 GB | 1770.6 GB |
| MXFP4 | 1608.9 GB | 1690.4 GB |
| Q5_K_M | 1977.2 GB | 2077.1 GB |
| Q6_K | 2279.5 GB | 2394.6 GB |
| Q8_0 | 2953.7 GB | 3102.4 GB |
| F16 | 5559.9 GB | 5838.9 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.44 GB | 0.23 GB | 0.12 GB |
| 8k | 0.88 GB | 0.47 GB | 0.25 GB |
| 16k | 1.76 GB | 0.93 GB | 0.49 GB |
| 32k | 3.51 GB | 1.87 GB | 0.99 GB |
| 64k | 7.02 GB | 3.73 GB | 1.97 GB |
| 128k | 14.04 GB | 7.46 GB | 3.95 GB |
From config.json: 93 KV-caching attention layers (MLA, 576-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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