Can I run gpt-oss-20b-heretic on a GeForce RTX 3080?
Not at these settings. No indexed quantization of gpt-oss-20b-heretic fits GeForce RTX 3080 at any context we compute, with q8_0 KV. The smallest shipped quantization is 10.73 GiB in weights alone, against 9.30 GiB usable. CPU offload can still run it, slowly.
Every quantization at every context
| Quant | Weights● | 4K◐ | 8K◐ | 16K◐ | 32K◐ | 64K◐ | 128K◐ |
|---|---|---|---|---|---|---|---|
| Q5_1 | 88.57 GiB | 89.4 | 89.5 | 89.6 | 89.8 | 90.2 | 91.0 |
| IQ4_NL | 67.58 GiB | 68.4 | 68.5 | 68.6 | 68.8 | 69.2 | 70.0 |
| BF16 | 38.99 GiB | 39.8 | 39.9 | 40.0 | 40.2 | 40.6 | 41.4 |
| Q8_0 | 20.73 GiB | 21.6 | 21.6 | 21.7 | 21.9 | 22.3 | 23.1 |
| Q6_K | 20.67 GiB | 21.5 | 21.6 | 21.7 | 21.9 | 22.3 | 23.1 |
| Q6_K_L | 20.67 GiB | 21.5 | 21.6 | 21.7 | 21.9 | 22.3 | 23.1 |
| Q5_K_L | 15.91 GiB | 16.8 | 16.8 | 16.9 | 17.1 | 17.5 | 18.3 |
| Q5_K_M | 15.74 GiB | 16.6 | 16.6 | 16.7 | 16.9 | 17.3 | 18.1 |
| Q4_K_L | 14.97 GiB | 15.8 | 15.9 | 16.0 | 16.2 | 16.6 | 17.4 |
| Q5_K_S | 14.81 GiB | 15.7 | 15.7 | 15.8 | 16.0 | 16.4 | 17.2 |
| Q4_K_M | 14.76 GiB | 15.6 | 15.7 | 15.8 | 16.0 | 16.4 | 17.2 |
| Q4_K_S | 13.83 GiB | 14.7 | 14.7 | 14.8 | 15.0 | 15.4 | 16.2 |
| Q3_K_L | 12.42 GiB | 13.3 | 13.3 | 13.4 | 13.6 | 14.0 | 14.8 |
| Q3_K_M | 12.03 GiB | 12.9 | 12.9 | 13.0 | 13.2 | 13.6 | 14.4 |
| IQ3_M | 11.69 GiB | 12.5 | 12.6 | 12.7 | 12.9 | 13.3 | 14.1 |
| Q2_K_L | 11.59 GiB | 12.4 | 12.5 | 12.6 | 12.8 | 13.2 | 14.0 |
| IQ4_XS | 11.40 GiB | 12.3 | 12.3 | 12.4 | 12.6 | 13.0 | 13.8 |
| IQ3_XS | 11.32 GiB | 12.2 | 12.2 | 12.3 | 12.5 | 12.9 | 13.7 |
| IQ3_XXS | 11.32 GiB | 12.2 | 12.2 | 12.3 | 12.5 | 12.9 | 13.7 |
| Q2_K | 11.32 GiB | 12.2 | 12.2 | 12.3 | 12.5 | 12.9 | 13.7 |
| Q3_K_S | 11.32 GiB | 12.2 | 12.2 | 12.3 | 12.5 | 12.9 | 13.7 |
| IQ2_M | 11.31 GiB | 12.2 | 12.2 | 12.3 | 12.5 | 12.9 | 13.7 |
| Q4_1 | 10.80 GiB | 11.6 | 11.7 | 11.8 | 12.0 | 12.4 | 13.2 |
| Q4_0 | 10.73 GiB | 11.6 | 11.6 | 11.7 | 11.9 | 12.3 | 13.1 |
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 128-token window rather than the full context.