Can I run Gemma-4-Giftige-Blume-31B-v2 on a Radeon RX 6500 XT?
Not at these settings. No indexed quantization of Gemma-4-Giftige-Blume-31B-v2 fits Radeon RX 6500 XT at any context we compute, with q8_0 KV. The smallest shipped quantization is 16.54 GiB in weights alone, against 3.72 GiB usable. CPU offload can still run it, slowly.
Every quantization at every context
| Quant | Weights● | 4K◐ | 8K◐ | 16K◐ | 32K◐ | 64K◐ | 128K◐ |
|---|---|---|---|---|---|---|---|
| Q8_0 | 30.39 GiB | 32.3 | 32.7 | 33.3 | 34.7 | 37.3 | 42.6 |
| Q6_K | 23.47 GiB | 25.4 | 25.7 | 26.4 | 27.7 | 30.4 | 35.7 |
| Q5_K_M | 20.35 GiB | 22.3 | 22.6 | 23.3 | 24.6 | 27.3 | 32.6 |
| Q5_K_S | 19.85 GiB | 21.8 | 22.1 | 22.8 | 24.1 | 26.8 | 32.1 |
| Q4_K_M | 17.40 GiB | 19.3 | 19.7 | 20.3 | 21.7 | 24.3 | 29.6 |
| Q4_K_S | 16.54 GiB | 18.5 | 18.8 | 19.5 | 20.8 | 23.5 | 28.8 |
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 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.