Can I run Phi-3.5-MoE-instruct on a Radeon RX 6500 XT?
Not at these settings. No indexed quantization of Phi-3.5-MoE-instruct fits Radeon RX 6500 XT at any context we compute, with q4_0 KV. The smallest shipped quantization is 10.27 GiB in weights alone, against 3.72 GiB usable. CPU offload can still run it, slowly.
Every quantization at every context
| Quant | Weights● | 4K◐ | 8K◐ | 16K◐ | 32K◐ | 64K◐ | 128K◐ |
|---|---|---|---|---|---|---|---|
| F16 | 78.00 GiB | 79.0 | 79.2 | 79.5 | 80.0 | 81.2 | 83.4 |
| Q8_0 | 41.44 GiB | 42.5 | 42.6 | 42.9 | 43.5 | 44.6 | 46.9 |
| Q6_K_L | 32.06 GiB | 33.1 | 33.2 | 33.5 | 34.1 | 35.2 | 37.5 |
| Q6_K | 32.00 GiB | 33.0 | 33.2 | 33.5 | 34.0 | 35.2 | 37.4 |
| Q5_K_L | 27.75 GiB | 28.8 | 28.9 | 29.2 | 29.8 | 30.9 | 33.2 |
| Q5_K_M | 27.68 GiB | 28.7 | 28.9 | 29.1 | 29.7 | 30.8 | 33.1 |
| Q5_K_S | 26.84 GiB | 27.9 | 28.0 | 28.3 | 28.9 | 30.0 | 32.2 |
| Q4_1 | 24.41 GiB | 25.5 | 25.6 | 25.9 | 26.4 | 27.6 | 29.8 |
| Q4_K_L | 23.70 GiB | 24.7 | 24.9 | 25.2 | 25.7 | 26.9 | 29.1 |
| Q4_K_M | 23.61 GiB | 24.7 | 24.8 | 25.1 | 25.6 | 26.8 | 29.0 |
| Q4_K_S | 22.18 GiB | 23.2 | 23.4 | 23.6 | 24.2 | 25.3 | 27.6 |
| Q4_0 | 22.08 GiB | 23.1 | 23.3 | 23.5 | 24.1 | 25.2 | 27.5 |
| IQ4_NL | 21.99 GiB | 23.0 | 23.2 | 23.5 | 24.0 | 25.2 | 27.4 |
| IQ4_XS | 20.78 GiB | 21.8 | 22.0 | 22.3 | 22.8 | 23.9 | 26.2 |
| Q3_K_L | 20.20 GiB | 21.2 | 21.4 | 21.7 | 22.2 | 23.4 | 25.6 |
| Q3_K_M | 18.66 GiB | 19.7 | 19.8 | 20.1 | 20.7 | 21.8 | 24.1 |
| IQ3_M | 17.11 GiB | 18.2 | 18.3 | 18.6 | 19.1 | 20.3 | 22.5 |
| Q3_K_S | 16.82 GiB | 17.9 | 18.0 | 18.3 | 18.8 | 20.0 | 22.2 |
| IQ3_XS | 15.92 GiB | 17.0 | 17.1 | 17.4 | 18.0 | 19.1 | 21.3 |
| Q2_K_L | 14.34 GiB | 15.4 | 15.5 | 15.8 | 16.4 | 17.5 | 19.7 |
| Q2_K | 14.22 GiB | 15.3 | 15.4 | 15.7 | 16.2 | 17.4 | 19.6 |
| IQ2_M | 12.82 GiB | 13.9 | 14.0 | 14.3 | 14.8 | 16.0 | 18.2 |
| IQ2_S | 11.67 GiB | 12.7 | 12.9 | 13.1 | 13.7 | 14.8 | 17.1 |
| IQ2_XS | 11.43 GiB | 12.5 | 12.6 | 12.9 | 13.5 | 14.6 | 16.8 |
| IQ2_XXS | 10.27 GiB | 11.3 | 11.5 | 11.7 | 12.3 | 13.4 | 15.7 |
Figures are GiB of total memory: weights plus KV cache plus compute buffer and backend overhead. Weights and KV are near-exact; the overhead term is modeled. Hover any cell for the breakdown.
Why other calculators disagree
A parameters × bits ÷ 8 estimate ignores two things that dominate at long context. First, the weights themselves are not the nominal rate — quantizations are mixtures, so the real file is consistently larger than the label implies. Second, most of this model's layers cache only a 131,072-token window rather than the full context.