Can I run Kimi Linear 48B A3B (MoE) locally?
Kimi Linear 48B A3B (MoE) has 49.12 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 32.0 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2025-10-30. 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 | 9.6 GB | 10.8 GB |
| IQ2_XXS | 12.6 GB | 14.0 GB |
| IQ2_M | 16.6 GB | 18.1 GB |
| Q2_K | 19.5 GB | 21.2 GB |
| IQ3_XXS | 18.8 GB | 20.5 GB |
| Q3_K_S | 22.4 GB | 24.3 GB |
| IQ3_M | 22.5 GB | 24.3 GB |
| Q3_K_M | 24.6 GB | 26.5 GB |
| IQ4_XS | 26.1 GB | 28.1 GB |
| Q4_0 | 27.6 GB | 29.7 GB |
| Q4_K_M | 29.8 GB | 32.0 GB |
| MXFP4 | 28.4 GB | 30.6 GB |
| Q5_K_M | 34.9 GB | 37.4 GB |
| Q6_K | 40.3 GB | 43.0 GB |
| Q8_0 | 52.2 GB | 55.5 GB |
| F16 | 98.2 GB | 103.9 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.13 GB | 0.07 GB | 0.04 GB |
| 8k | 0.25 GB | 0.14 GB | 0.07 GB |
| 16k | 0.51 GB | 0.27 GB | 0.14 GB |
| 32k | 1.02 GB | 0.54 GB | 0.29 GB |
| 64k | 2.04 GB | 1.08 GB | 0.57 GB |
| 128k | 4.08 GB | 2.17 GB | 1.15 GB |
From config.json: 27 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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