Does Qwen2.5-Coder-32B-Instruct fit in 8GB of VRAM?
Not at these settings. No indexed quantization of Qwen2.5-Coder-32B-Instruct fits 8GB card at any context we compute, with q4_0 KV. The smallest shipped quantization is 8.41 GiB in weights alone, against 7.44 GiB usable. CPU offload can still run it, slowly.
Every quantization at every context
| Quant | Weights● | 4K◐ | 8K◐ | 16K◐ | 32K◐ | 64K◐ | 128K◐ |
|---|---|---|---|---|---|---|---|
| Q8_0 | 64.86 GiB | 66.0 | 66.3 | 66.9 | 68.0 | 70.3 | 74.8 |
| Q6_K | 50.08 GiB | 51.3 | 51.5 | 52.1 | 53.2 | 55.5 | 60.0 |
| Q5_K_M | 43.33 GiB | 44.5 | 44.8 | 45.4 | 46.5 | 48.7 | 53.2 |
| Q5_0 | 42.17 GiB | 43.3 | 43.6 | 44.2 | 45.3 | 47.6 | 52.1 |
| Q4_K_M | 36.98 GiB | 38.2 | 38.4 | 39.0 | 40.1 | 42.4 | 46.9 |
| Q4_0 | 34.72 GiB | 35.9 | 36.2 | 36.7 | 37.9 | 40.1 | 44.6 |
| Q3_K_M | 29.68 GiB | 30.9 | 31.1 | 31.7 | 32.8 | 35.1 | 39.6 |
| Q6_K_L | 25.39 GiB | 26.6 | 26.9 | 27.4 | 28.5 | 30.8 | 35.3 |
| Q2_K | 22.93 GiB | 24.1 | 24.4 | 25.0 | 26.1 | 28.3 | 32.8 |
| Q5_K_L | 22.11 GiB | 23.3 | 23.6 | 24.1 | 25.3 | 27.5 | 32.0 |
| Q5_K_S | 21.08 GiB | 22.3 | 22.5 | 23.1 | 24.2 | 26.5 | 31.0 |
| Q4_K_L | 19.03 GiB | 20.2 | 20.5 | 21.1 | 22.2 | 24.4 | 28.9 |
| Q4_K_S | 17.49 GiB | 18.7 | 19.0 | 19.5 | 20.6 | 22.9 | 27.4 |
| IQ4_NL | 17.40 GiB | 18.6 | 18.9 | 19.4 | 20.5 | 22.8 | 27.3 |
| IQ4_XS | 16.48 GiB | 17.7 | 17.9 | 18.5 | 19.6 | 21.9 | 26.4 |
| Q3_K_L | 16.06 GiB | 17.2 | 17.5 | 18.1 | 19.2 | 21.5 | 26.0 |
| IQ3_M | 13.79 GiB | 15.0 | 15.3 | 15.8 | 16.9 | 19.2 | 23.7 |
| Q3_K_S | 13.40 GiB | 14.6 | 14.9 | 15.4 | 16.6 | 18.8 | 23.3 |
| IQ3_XS | 12.76 GiB | 13.9 | 14.2 | 14.8 | 15.9 | 18.2 | 22.7 |
| Q2_K_L | 12.18 GiB | 13.4 | 13.6 | 14.2 | 15.3 | 17.6 | 22.1 |
| IQ3_XXS | 11.96 GiB | 13.1 | 13.4 | 14.0 | 15.1 | 17.4 | 21.9 |
| IQ2_M | 10.49 GiB | 11.7 | 12.0 | 12.5 | 13.6 | 15.9 | 20.4 |
| IQ2_S | 9.67 GiB | 10.9 | 11.1 | 11.7 | 12.8 | 15.1 | 19.6 |
| IQ2_XS | 9.27 GiB | 10.5 | 10.7 | 11.3 | 12.4 | 14.7 | 19.2 |
| IQ2_XXS | 8.41 GiB | 9.6 | 9.9 | 10.4 | 11.6 | 13.8 | 18.3 |
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 there are no speeds on this page
A capacity is not a card. Whether a model fits depends only on memory, so every figure above holds for any 8GB accelerator. How fast it runs depends on memory bandwidth, which varies several-fold between cards of the same capacity — so putting a tokens-per-second number here would be inventing one. Pick a specific card from hardware and the speed column appears.
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.