Does G4-MeroMero-31B-StyleSwap fit in 8GB of VRAM?
Not at these settings. No indexed quantization of G4-MeroMero-31B-StyleSwap fits 8GB card at any context we compute, with q8_0 KV. The smallest shipped quantization is 7.10 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 | 31.79 GiB | 33.6 | 34.0 | 34.6 | 35.9 | 38.6 | 43.9 |
| I1-Q6_K | 24.55 GiB | 26.4 | 26.7 | 27.4 | 28.7 | 31.4 | 36.7 |
| Q6_K | 24.55 GiB | 26.4 | 26.7 | 27.4 | 28.7 | 31.4 | 36.7 |
| I1-Q5_K_M | 21.25 GiB | 23.1 | 23.4 | 24.1 | 25.4 | 28.1 | 33.4 |
| Q5_K_M | 21.25 GiB | 23.1 | 23.4 | 24.1 | 25.4 | 28.1 | 33.4 |
| I1-Q5_K_S | 20.75 GiB | 22.6 | 22.9 | 23.6 | 24.9 | 27.6 | 32.9 |
| Q5_K_S | 20.75 GiB | 22.6 | 22.9 | 23.6 | 24.9 | 27.6 | 32.9 |
| I1-Q4_1 | 18.96 GiB | 20.8 | 21.1 | 21.8 | 23.1 | 25.8 | 31.1 |
| I1-Q4_K_M | 18.14 GiB | 20.0 | 20.3 | 21.0 | 22.3 | 25.0 | 30.3 |
| Q4_K_M | 18.14 GiB | 20.0 | 20.3 | 21.0 | 22.3 | 25.0 | 30.3 |
| I1-Q4_K_S | 17.28 GiB | 19.1 | 19.4 | 20.1 | 21.4 | 24.1 | 29.4 |
| Q4_K_S | 17.28 GiB | 19.1 | 19.4 | 20.1 | 21.4 | 24.1 | 29.4 |
| I1-Q4_0 | 17.22 GiB | 19.1 | 19.4 | 20.1 | 21.4 | 24.0 | 29.4 |
| IQ4_XS | 16.40 GiB | 18.2 | 18.6 | 19.2 | 20.6 | 23.2 | 28.5 |
| I1-IQ4_XS | 16.28 GiB | 18.1 | 18.5 | 19.1 | 20.4 | 23.1 | 28.4 |
| I1-Q3_K_L | 16.05 GiB | 17.9 | 18.2 | 18.9 | 20.2 | 22.9 | 28.2 |
| Q3_K_L | 16.05 GiB | 17.9 | 18.2 | 18.9 | 20.2 | 22.9 | 28.2 |
| I1-Q3_K_M | 14.80 GiB | 16.6 | 17.0 | 17.6 | 19.0 | 21.6 | 26.9 |
| Q3_K_M | 14.80 GiB | 16.6 | 17.0 | 17.6 | 19.0 | 21.6 | 26.9 |
| I1-IQ3_M | 14.00 GiB | 15.8 | 16.2 | 16.8 | 18.2 | 20.8 | 26.1 |
| I1-IQ3_S | 13.38 GiB | 15.2 | 15.5 | 16.2 | 17.5 | 20.2 | 25.5 |
| I1-Q3_K_S | 13.38 GiB | 15.2 | 15.5 | 16.2 | 17.5 | 20.2 | 25.5 |
| Q3_K_S | 13.38 GiB | 15.2 | 15.5 | 16.2 | 17.5 | 20.2 | 25.5 |
| I1-IQ3_XS | 12.74 GiB | 14.6 | 14.9 | 15.6 | 16.9 | 19.6 | 24.9 |
| I1-IQ3_XXS | 11.81 GiB | 13.6 | 14.0 | 14.6 | 16.0 | 18.6 | 23.9 |
| I1-Q2_K | 11.53 GiB | 13.4 | 13.7 | 14.4 | 15.7 | 18.3 | 23.7 |
| Q2_K | 11.53 GiB | 13.4 | 13.7 | 14.4 | 15.7 | 18.3 | 23.7 |
| I1-IQ2_M | 10.73 GiB | 12.6 | 12.9 | 13.6 | 14.9 | 17.5 | 22.9 |
| I1-Q2_K_S | 10.65 GiB | 12.5 | 12.8 | 13.5 | 14.8 | 17.5 | 22.8 |
| I1-IQ2_S | 10.02 GiB | 11.9 | 12.2 | 12.9 | 14.2 | 16.8 | 22.2 |
| I1-IQ2_XS | 9.31 GiB | 11.1 | 11.5 | 12.1 | 13.5 | 16.1 | 21.4 |
| I1-IQ2_XXS | 8.51 GiB | 10.3 | 10.7 | 11.3 | 12.7 | 15.3 | 20.6 |
| I1-IQ1_M | 7.63 GiB | 9.5 | 9.8 | 10.5 | 11.8 | 14.4 | 19.8 |
| I1-IQ1_S | 7.10 GiB | 8.9 | 9.3 | 9.9 | 11.3 | 13.9 | 19.2 |
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.