Can I run Qwen3 30B A3B (2507) (MoE) locally?
Qwen3 30B A3B (2507) (MoE) has 30.53 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 20.4 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2025-07-28. 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 | 6.0 GB | 7.3 GB |
| IQ2_XXS | 7.9 GB | 9.3 GB |
| IQ2_M | 10.3 GB | 11.8 GB |
| Q2_K | 12.1 GB | 13.7 GB |
| IQ3_XXS | 11.7 GB | 13.3 GB |
| Q3_K_S | 13.9 GB | 15.6 GB |
| IQ3_M | 14.0 GB | 15.7 GB |
| Q3_K_M | 15.3 GB | 17.0 GB |
| IQ4_XS | 16.2 GB | 18.0 GB |
| Q4_0 | 17.2 GB | 19.0 GB |
| Q4_K_M | 18.5 GB | 20.4 GB |
| MXFP4 | 17.7 GB | 19.6 GB |
| Q5_K_M | 21.7 GB | 23.8 GB |
| Q6_K | 25.0 GB | 27.3 GB |
| Q8_0 | 32.4 GB | 35.1 GB |
| F16 | 61.1 GB | 65.1 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.40 GB | 0.21 GB | 0.11 GB |
| 8k | 0.81 GB | 0.43 GB | 0.23 GB |
| 16k | 1.61 GB | 0.86 GB | 0.45 GB |
| 32k | 3.22 GB | 1.71 GB | 0.91 GB |
| 64k | 6.44 GB | 3.42 GB | 1.81 GB |
| 128k | 12.88 GB | 6.85 GB | 3.62 GB |
From config.json: 48 KV-caching attention layers, 4 KV heads × 128 head dim. Max context 256k. 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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