Can I run DeepSeek V4 Pro (MoE) locally?
DeepSeek V4 Pro (MoE) has 1598.84 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 1018.9 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2026-04-22. 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 | 311.8 GB | 328.5 GB |
| IQ2_XXS | 411.7 GB | 433.4 GB |
| IQ2_M | 539.6 GB | 567.7 GB |
| Q2_K | 633.5 GB | 666.3 GB |
| IQ3_XXS | 611.6 GB | 643.2 GB |
| Q3_K_S | 729.5 GB | 767.1 GB |
| IQ3_M | 731.5 GB | 769.2 GB |
| Q3_K_M | 799.4 GB | 840.5 GB |
| IQ4_XS | 849.4 GB | 893.0 GB |
| Q4_0 | 899.3 GB | 945.4 GB |
| Q4_K_M | 969.3 GB | 1018.9 GB |
| MXFP4 | 925.3 GB | 972.7 GB |
| Q5_K_M | 1137.2 GB | 1195.1 GB |
| Q6_K | 1311.0 GB | 1377.7 GB |
| Q8_0 | 1698.8 GB | 1784.8 GB |
| F16 | 3197.7 GB | 3358.7 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.51 GB | 0.27 GB | 0.14 GB |
| 8k | 1.02 GB | 0.54 GB | 0.29 GB |
| 16k | 2.05 GB | 1.09 GB | 0.58 GB |
| 32k | 4.09 GB | 2.17 GB | 1.15 GB |
| 64k | 8.19 GB | 4.35 GB | 2.30 GB |
| 128k | 16.37 GB | 8.70 GB | 4.61 GB |
From config.json: 61 KV-caching attention layers, 1 KV heads × 512 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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