Does gemma-4-26B-A4B-it-qat-q4_0-unquantized-uncensored-heretic fit in 8GB of VRAM?
Not at these settings. No indexed quantization of gemma-4-26B-A4B-it-qat-q4_0-unquantized-uncensored-heretic fits 8GB card at any context we compute, with q8_0 KV. The smallest shipped quantization is 14.93 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◐ |
|---|---|---|---|---|---|---|---|
| NVFP4 | 16.46 GiB | 17.5 | 17.6 | 17.7 | 18.1 | 18.7 | 20.1 |
| Q4_0 | 14.93 GiB | 16.0 | 16.0 | 16.2 | 16.5 | 17.2 | 18.5 |
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.