Does gemma-4-A4B-98e-v6-coder-it fit in 8GB of VRAM?
Not at these settings. No indexed quantization of gemma-4-A4B-98e-v6-coder-it fits 8GB card at any context we compute, with q8_0 KV. The smallest shipped quantization is 7.24 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◐ |
|---|---|---|---|---|---|---|---|
| F16 | 37.06 GiB | 38.1 | 38.2 | 38.3 | 38.7 | 39.3 | 40.7 |
| Q6_K | 31.05 GiB | 32.1 | 32.2 | 32.3 | 32.7 | 33.3 | 34.6 |
| Q5_K_M | 26.21 GiB | 27.2 | 27.3 | 27.5 | 27.8 | 28.5 | 29.8 |
| Q4_K_M | 22.25 GiB | 23.3 | 23.4 | 23.5 | 23.9 | 24.5 | 25.8 |
| Q8_0 | 19.71 GiB | 20.7 | 20.8 | 21.0 | 21.3 | 22.0 | 23.3 |
| Q6_K_L | 16.75 GiB | 17.8 | 17.9 | 18.0 | 18.4 | 19.0 | 20.3 |
| Q5_K_L | 14.20 GiB | 15.2 | 15.3 | 15.5 | 15.8 | 16.5 | 17.8 |
| Q5_K_S | 13.21 GiB | 14.2 | 14.3 | 14.5 | 14.8 | 15.5 | 16.8 |
| Q4_K_L | 12.50 GiB | 13.5 | 13.6 | 13.8 | 14.1 | 14.8 | 16.1 |
| Q4_1 | 11.75 GiB | 12.8 | 12.9 | 13.0 | 13.4 | 14.0 | 15.3 |
| Q4_K_S | 11.37 GiB | 12.4 | 12.5 | 12.6 | 13.0 | 13.6 | 15.0 |
| IQ4_NL | 10.63 GiB | 11.7 | 11.7 | 11.9 | 12.2 | 12.9 | 14.2 |
| Q4_0 | 10.63 GiB | 11.7 | 11.7 | 11.9 | 12.2 | 12.9 | 14.2 |
| IQ4_XS | 10.25 GiB | 11.3 | 11.4 | 11.5 | 11.9 | 12.5 | 13.9 |
| Q3_K_L | 10.19 GiB | 11.2 | 11.3 | 11.5 | 11.8 | 12.5 | 13.8 |
| Q3_K_M | 9.79 GiB | 10.8 | 10.9 | 11.1 | 11.4 | 12.1 | 13.4 |
| IQ3_M | 9.15 GiB | 10.2 | 10.3 | 10.4 | 10.8 | 11.4 | 12.7 |
| Q3_K_S | 9.01 GiB | 10.0 | 10.1 | 10.3 | 10.6 | 11.3 | 12.6 |
| IQ3_XS | 8.58 GiB | 9.6 | 9.7 | 9.9 | 10.2 | 10.9 | 12.2 |
| IQ3_XXS | 8.33 GiB | 9.4 | 9.4 | 9.6 | 9.9 | 10.6 | 11.9 |
| IQ2_M | 7.66 GiB | 8.7 | 8.8 | 8.9 | 9.3 | 9.9 | 11.3 |
| IQ2_S | 7.29 GiB | 8.3 | 8.4 | 8.6 | 8.9 | 9.6 | 10.9 |
| IQ2_XS | 7.24 GiB | 8.3 | 8.3 | 8.5 | 8.8 | 9.5 | 10.8 |
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.