Does Gemma4-Gutenberg-31B fit in 8GB of VRAM?
Not at these settings. No indexed quantization of Gemma4-Gutenberg-31B fits 8GB card at any context we compute, with q4_0 KV. The smallest shipped quantization is 6.67 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◐ |
|---|---|---|---|---|---|---|---|
| BF16 | 57.20 GiB | 58.6 | 58.8 | 59.1 | 59.8 | 61.2 | 64.0 |
| Q8_0 | 30.39 GiB | 31.8 | 32.0 | 32.3 | 33.0 | 34.4 | 37.2 |
| Q6_K_L | 25.21 GiB | 26.6 | 26.8 | 27.1 | 27.8 | 29.2 | 32.0 |
| Q6_K | 24.89 GiB | 26.3 | 26.5 | 26.8 | 27.5 | 28.9 | 31.7 |
| I1-Q6_K | 23.47 GiB | 24.9 | 25.0 | 25.4 | 26.1 | 27.5 | 30.3 |
| Q5_K_L | 21.37 GiB | 22.8 | 22.9 | 23.3 | 24.0 | 25.4 | 28.2 |
| Q5_K_M | 21.06 GiB | 22.4 | 22.6 | 23.0 | 23.7 | 25.1 | 27.9 |
| I1-Q5_K_M | 20.35 GiB | 21.7 | 21.9 | 22.3 | 23.0 | 24.4 | 27.2 |
| Q5_K_S | 20.03 GiB | 21.4 | 21.6 | 21.9 | 22.6 | 24.1 | 26.9 |
| I1-Q5_K_S | 19.85 GiB | 21.2 | 21.4 | 21.8 | 22.5 | 23.9 | 26.7 |
| Q4_K_L | 18.57 GiB | 20.0 | 20.1 | 20.5 | 21.2 | 22.6 | 25.4 |
| Q4_1 | 18.41 GiB | 19.8 | 20.0 | 20.3 | 21.0 | 22.4 | 25.2 |
| Q4_K_M | 18.25 GiB | 19.6 | 19.8 | 20.2 | 20.9 | 22.3 | 25.1 |
| I1-Q4_1 | 18.14 GiB | 19.5 | 19.7 | 20.1 | 20.8 | 22.2 | 25.0 |
| I1-Q4_K_M | 17.40 GiB | 18.8 | 19.0 | 19.3 | 20.0 | 21.4 | 24.2 |
| Q4_K_S | 16.95 GiB | 18.3 | 18.5 | 18.9 | 19.6 | 21.0 | 23.8 |
| Q4_0 | 16.83 GiB | 18.2 | 18.4 | 18.7 | 19.5 | 20.9 | 23.7 |
| IQ4_NL | 16.79 GiB | 18.2 | 18.3 | 18.7 | 19.4 | 20.8 | 23.6 |
| I1-Q4_K_S | 16.54 GiB | 17.9 | 18.1 | 18.5 | 19.2 | 20.6 | 23.4 |
| I1-Q4_0 | 16.49 GiB | 17.9 | 18.0 | 18.4 | 19.1 | 20.5 | 23.3 |
| IQ4_XS | 15.98 GiB | 17.4 | 17.5 | 17.9 | 18.6 | 20.0 | 22.8 |
| Q3_K_L | 15.66 GiB | 17.0 | 17.2 | 17.6 | 18.3 | 19.7 | 22.5 |
| I1-IQ4_XS | 15.59 GiB | 17.0 | 17.1 | 17.5 | 18.2 | 19.6 | 22.4 |
| I1-Q3_K_L | 15.49 GiB | 16.9 | 17.0 | 17.4 | 18.1 | 19.5 | 22.3 |
| Q3_K_M | 14.82 GiB | 16.2 | 16.4 | 16.7 | 17.4 | 18.8 | 21.7 |
| I1-Q3_K_M | 14.24 GiB | 15.6 | 15.8 | 16.2 | 16.9 | 18.3 | 21.1 |
| IQ3_M | 14.09 GiB | 15.5 | 15.7 | 16.0 | 16.7 | 18.1 | 20.9 |
| I1-IQ3_M | 13.43 GiB | 14.8 | 15.0 | 15.3 | 16.1 | 17.5 | 20.3 |
| Q3_K_S | 13.34 GiB | 14.7 | 14.9 | 15.3 | 16.0 | 17.4 | 20.2 |
| IQ3_XS | 12.89 GiB | 14.3 | 14.5 | 14.8 | 15.5 | 16.9 | 19.7 |
| I1-IQ3_S | 12.82 GiB | 14.2 | 14.4 | 14.7 | 15.4 | 16.8 | 19.7 |
| I1-Q3_K_S | 12.82 GiB | 14.2 | 14.4 | 14.7 | 15.4 | 16.8 | 19.7 |
| I1-IQ3_XS | 12.17 GiB | 13.6 | 13.7 | 14.1 | 14.8 | 16.2 | 19.0 |
| IQ3_XXS | 12.09 GiB | 13.5 | 13.7 | 14.0 | 14.7 | 16.1 | 18.9 |
| Q2_K_L | 12.08 GiB | 13.5 | 13.6 | 14.0 | 14.7 | 16.1 | 18.9 |
| IQ2_M | 11.78 GiB | 13.2 | 13.3 | 13.7 | 14.4 | 15.8 | 18.6 |
| Q2_K | 11.76 GiB | 13.2 | 13.3 | 13.7 | 14.4 | 15.8 | 18.6 |
| I1-IQ3_XXS | 11.25 GiB | 12.6 | 12.8 | 13.2 | 13.9 | 15.3 | 18.1 |
| IQ2_S | 11.25 GiB | 12.6 | 12.8 | 13.2 | 13.9 | 15.3 | 18.1 |
| I1-Q2_K | 11.10 GiB | 12.5 | 12.7 | 13.0 | 13.7 | 15.1 | 17.9 |
| IQ2_XS | 10.71 GiB | 12.1 | 12.3 | 12.6 | 13.3 | 14.7 | 17.5 |
| I1-Q2_K_S | 10.22 GiB | 11.6 | 11.8 | 12.1 | 12.8 | 14.2 | 17.1 |
| I1-IQ2_M | 10.17 GiB | 11.6 | 11.7 | 12.1 | 12.8 | 14.2 | 17.0 |
| IQ2_XXS | 10.09 GiB | 11.5 | 11.6 | 12.0 | 12.7 | 14.1 | 16.9 |
| I1-IQ2_S | 9.46 GiB | 10.8 | 11.0 | 11.4 | 12.1 | 13.5 | 16.3 |
| I1-IQ2_XS | 8.88 GiB | 10.3 | 10.4 | 10.8 | 11.5 | 12.9 | 15.7 |
| I1-IQ2_XXS | 8.08 GiB | 9.5 | 9.6 | 10.0 | 10.7 | 12.1 | 14.9 |
| I1-IQ1_M | 7.20 GiB | 8.6 | 8.8 | 9.1 | 9.8 | 11.2 | 14.0 |
| I1-IQ1_S | 6.67 GiB | 8.1 | 8.2 | 8.6 | 9.3 | 10.7 | 13.5 |
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 1,024-token window rather than the full context.