Can I run Malaysian-Qwen2.5-72B-Instruct on a Radeon RX 6500 XT?
Not at these settings. No indexed quantization of Malaysian-Qwen2.5-72B-Instruct fits Radeon RX 6500 XT at any context we compute, with q4_0 KV. The smallest shipped quantization is 21.13 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◐ |
|---|---|---|---|---|---|---|---|
| I1-Q4_K_M | 44.16 GiB | 45.5 | 45.9 | 46.6 | 48.0 | 50.8 | 56.4 |
| I1-Q4_1 | 42.56 GiB | 43.9 | 44.3 | 45.0 | 46.4 | 49.2 | 54.8 |
| I1-Q4_K_S | 40.88 GiB | 42.3 | 42.6 | 43.3 | 44.7 | 47.5 | 53.2 |
| I1-Q4_0 | 38.54 GiB | 39.9 | 40.3 | 41.0 | 42.4 | 45.2 | 50.8 |
| I1-IQ4_XS | 36.98 GiB | 38.4 | 38.7 | 39.4 | 40.8 | 43.6 | 49.3 |
| I1-Q3_K_L | 36.79 GiB | 38.2 | 38.5 | 39.2 | 40.6 | 43.4 | 49.1 |
| I1-Q3_K_M | 35.11 GiB | 36.5 | 36.8 | 37.5 | 39.0 | 41.8 | 47.4 |
| I1-IQ3_M | 33.07 GiB | 34.4 | 34.8 | 35.5 | 36.9 | 39.7 | 45.3 |
| I1-IQ3_S | 32.12 GiB | 33.5 | 33.9 | 34.6 | 36.0 | 38.8 | 44.4 |
| I1-Q3_K_S | 32.12 GiB | 33.5 | 33.9 | 34.6 | 36.0 | 38.8 | 44.4 |
| I1-IQ3_XS | 30.59 GiB | 32.0 | 32.3 | 33.0 | 34.4 | 37.2 | 42.9 |
| I1-IQ3_XXS | 29.66 GiB | 31.0 | 31.4 | 32.1 | 33.5 | 36.3 | 41.9 |
| I1-Q2_K | 27.76 GiB | 29.1 | 29.5 | 30.2 | 31.6 | 34.4 | 40.0 |
| I1-Q2_K_S | 27.54 GiB | 28.9 | 29.3 | 30.0 | 31.4 | 34.2 | 39.8 |
| I1-IQ2_M | 27.32 GiB | 28.7 | 29.1 | 29.8 | 31.2 | 34.0 | 39.6 |
| I1-IQ2_S | 26.02 GiB | 27.4 | 27.8 | 28.5 | 29.9 | 32.7 | 38.3 |
| I1-IQ2_XS | 25.20 GiB | 26.6 | 26.9 | 27.6 | 29.0 | 31.9 | 37.5 |
| I1-IQ2_XXS | 23.74 GiB | 25.1 | 25.5 | 26.2 | 27.6 | 30.4 | 36.0 |
| I1-IQ1_M | 22.11 GiB | 23.5 | 23.8 | 24.5 | 26.0 | 28.8 | 34.4 |
| I1-IQ1_S | 21.13 GiB | 22.5 | 22.9 | 23.6 | 25.0 | 27.8 | 33.4 |
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.