Does Equinox-31B fit in 12GB of VRAM?
Not at these settings. No indexed quantization of Equinox-31B fits 12GB card at any context we compute, with q8_0 KV. The smallest shipped quantization is 10.09 GiB in weights alone, against 11.16 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 | 59.0 | 59.4 | 60.0 | 61.4 | 64.0 | 69.3 |
| Q8_0 | 30.39 GiB | 32.2 | 32.6 | 33.2 | 34.6 | 37.2 | 42.5 |
| Q6_K_L | 25.21 GiB | 27.0 | 27.4 | 28.0 | 29.4 | 32.0 | 37.3 |
| Q6_K | 24.89 GiB | 26.7 | 27.1 | 27.7 | 29.1 | 31.7 | 37.0 |
| Q5_K_L | 21.37 GiB | 23.2 | 23.5 | 24.2 | 25.5 | 28.2 | 33.5 |
| Q5_K_M | 21.06 GiB | 22.9 | 23.2 | 23.9 | 25.2 | 27.9 | 33.2 |
| Q5_K_S | 20.03 GiB | 21.9 | 22.2 | 22.9 | 24.2 | 26.8 | 32.2 |
| Q4_K_L | 18.57 GiB | 20.4 | 20.7 | 21.4 | 22.7 | 25.4 | 30.7 |
| Q4_1 | 18.41 GiB | 20.2 | 20.6 | 21.2 | 22.6 | 25.2 | 30.5 |
| Q4_K_M | 18.25 GiB | 20.1 | 20.4 | 21.1 | 22.4 | 25.1 | 30.4 |
| Q4_K_S | 16.95 GiB | 18.8 | 19.1 | 19.8 | 21.1 | 23.8 | 29.1 |
| Q4_0 | 16.83 GiB | 18.7 | 19.0 | 19.7 | 21.0 | 23.7 | 29.0 |
| IQ4_NL | 16.79 GiB | 18.6 | 19.0 | 19.6 | 20.9 | 23.6 | 28.9 |
| IQ4_XS | 15.98 GiB | 17.8 | 18.1 | 18.8 | 20.1 | 22.8 | 28.1 |
| Q3_K_L | 15.66 GiB | 17.5 | 17.8 | 18.5 | 19.8 | 22.5 | 27.8 |
| Q3_K_M | 14.82 GiB | 16.7 | 17.0 | 17.7 | 19.0 | 21.6 | 27.0 |
| IQ3_M | 14.09 GiB | 15.9 | 16.3 | 16.9 | 18.3 | 20.9 | 26.2 |
| Q3_K_S | 13.34 GiB | 15.2 | 15.5 | 16.2 | 17.5 | 20.2 | 25.5 |
| IQ3_XS | 12.89 GiB | 14.7 | 15.1 | 15.7 | 17.1 | 19.7 | 25.0 |
| IQ3_XXS | 12.09 GiB | 13.9 | 14.3 | 14.9 | 16.2 | 18.9 | 24.2 |
| Q2_K_L | 12.08 GiB | 13.9 | 14.2 | 14.9 | 16.2 | 18.9 | 24.2 |
| IQ2_M | 11.78 GiB | 13.6 | 13.9 | 14.6 | 15.9 | 18.6 | 23.9 |
| Q2_K | 11.76 GiB | 13.6 | 13.9 | 14.6 | 15.9 | 18.6 | 23.9 |
| IQ2_S | 11.25 GiB | 13.1 | 13.4 | 14.1 | 15.4 | 18.1 | 23.4 |
| IQ2_XS | 10.71 GiB | 12.5 | 12.9 | 13.5 | 14.9 | 17.5 | 22.8 |
| Q2_K_S | 10.22 GiB | 12.1 | 12.4 | 13.1 | 14.4 | 17.0 | 22.4 |
| IQ2_XXS | 10.09 GiB | 11.9 | 12.3 | 12.9 | 14.2 | 16.9 | 22.2 |
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 12GB 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.