Does XMainframe-v2-Instruct-32b fit in 8GB of VRAM?
Not at these settings. No indexed quantization of XMainframe-v2-Instruct-32b fits 8GB card at any context we compute, with q4_0 KV. The smallest shipped quantization is 6.77 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◐ |
|---|---|---|---|---|---|---|---|
| I1-Q6_K | 25.04 GiB | 26.2 | 26.5 | 27.1 | 28.2 | 30.4 | 34.9 |
| I1-Q5_K_M | 21.66 GiB | 22.8 | 23.1 | 23.7 | 24.8 | 27.1 | 31.6 |
| I1-Q5_K_S | 21.08 GiB | 22.3 | 22.5 | 23.1 | 24.2 | 26.5 | 31.0 |
| I1-Q4_1 | 19.22 GiB | 20.4 | 20.7 | 21.2 | 22.4 | 24.6 | 29.1 |
| I1-Q4_K_M | 18.49 GiB | 19.7 | 19.9 | 20.5 | 21.6 | 23.9 | 28.4 |
| I1-Q4_K_S | 17.49 GiB | 18.7 | 19.0 | 19.5 | 20.6 | 22.9 | 27.4 |
| I1-Q4_0 | 17.43 GiB | 18.6 | 18.9 | 19.5 | 20.6 | 22.8 | 27.3 |
| I1-IQ4_XS | 16.48 GiB | 17.7 | 17.9 | 18.5 | 19.6 | 21.9 | 26.4 |
| I1-Q3_K_L | 16.06 GiB | 17.2 | 17.5 | 18.1 | 19.2 | 21.5 | 26.0 |
| I1-Q3_K_M | 14.84 GiB | 16.0 | 16.3 | 16.9 | 18.0 | 20.2 | 24.7 |
| I1-IQ3_M | 13.79 GiB | 15.0 | 15.3 | 15.8 | 16.9 | 19.2 | 23.7 |
| I1-IQ3_S | 13.45 GiB | 14.6 | 14.9 | 15.5 | 16.6 | 18.8 | 23.3 |
| I1-Q3_K_S | 13.40 GiB | 14.6 | 14.9 | 15.4 | 16.6 | 18.8 | 23.3 |
| I1-IQ3_XS | 12.76 GiB | 13.9 | 14.2 | 14.8 | 15.9 | 18.2 | 22.7 |
| I1-IQ3_XXS | 11.96 GiB | 13.1 | 13.4 | 14.0 | 15.1 | 17.4 | 21.9 |
| I1-Q2_K | 11.47 GiB | 12.6 | 12.9 | 13.5 | 14.6 | 16.9 | 21.4 |
| I1-Q2_K_S | 10.70 GiB | 11.9 | 12.2 | 12.7 | 13.8 | 16.1 | 20.6 |
| I1-IQ2_M | 10.49 GiB | 11.7 | 12.0 | 12.5 | 13.6 | 15.9 | 20.4 |
| I1-IQ2_S | 9.67 GiB | 10.9 | 11.1 | 11.7 | 12.8 | 15.1 | 19.6 |
| I1-IQ2_XS | 9.27 GiB | 10.5 | 10.7 | 11.3 | 12.4 | 14.7 | 19.2 |
| I1-IQ2_XXS | 8.41 GiB | 9.6 | 9.9 | 10.4 | 11.6 | 13.8 | 18.3 |
| I1-IQ1_M | 7.39 GiB | 8.6 | 8.8 | 9.4 | 10.5 | 12.8 | 17.3 |
| I1-IQ1_S | 6.77 GiB | 8.0 | 8.2 | 8.8 | 9.9 | 12.2 | 16.7 |
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 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.