Can I run Hy3 (MoE) locally?
Hy3 (MoE) has 298.79 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 192.1 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2026-07-02. 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 | 58.3 GB | 63.1 GB |
| IQ2_XXS | 76.9 GB | 82.7 GB |
| IQ2_M | 100.8 GB | 107.8 GB |
| Q2_K | 118.4 GB | 126.3 GB |
| IQ3_XXS | 114.3 GB | 121.9 GB |
| Q3_K_S | 136.3 GB | 145.1 GB |
| IQ3_M | 136.7 GB | 145.5 GB |
| Q3_K_M | 149.4 GB | 158.8 GB |
| IQ4_XS | 158.7 GB | 168.6 GB |
| Q4_0 | 168.1 GB | 178.4 GB |
| Q4_K_M | 181.1 GB | 192.1 GB |
| MXFP4 | 172.9 GB | 183.5 GB |
| Q5_K_M | 212.5 GB | 225.1 GB |
| Q6_K | 245.0 GB | 259.2 GB |
| Q8_0 | 317.5 GB | 335.3 GB |
| F16 | 597.6 GB | 629.4 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 1.34 GB | 0.71 GB | 0.38 GB |
| 8k | 2.68 GB | 1.43 GB | 0.75 GB |
| 16k | 5.37 GB | 2.85 GB | 1.51 GB |
| 32k | 10.74 GB | 5.70 GB | 3.02 GB |
| 64k | 21.47 GB | 11.41 GB | 6.04 GB |
| 128k | 42.95 GB | 22.82 GB | 12.08 GB |
From config.json: 80 KV-caching attention layers, 8 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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