Does EXAONE-4.0-32B fit in 8GB of VRAM?
Not at these settings. No indexed quantization of EXAONE-4.0-32B fits 8GB card at any context we compute, with q4_0 KV. The smallest shipped quantization is 8.96 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◐ |
|---|---|---|---|---|---|---|---|
| BF16 | 59.62 GiB | 60.8 | 60.9 | 61.0 | 61.3 | 61.9 | 63.0 |
| Q8_0 | 31.67 GiB | 32.9 | 32.9 | 33.1 | 33.4 | 33.9 | 35.1 |
| Q6_K_L | 24.69 GiB | 25.9 | 26.0 | 26.1 | 26.4 | 27.0 | 28.1 |
| Q6_K | 24.46 GiB | 25.6 | 25.7 | 25.9 | 26.2 | 26.7 | 27.8 |
| Q5_K_L | 21.44 GiB | 22.6 | 22.7 | 22.9 | 23.1 | 23.7 | 24.8 |
| Q5_K_M | 21.14 GiB | 22.3 | 22.4 | 22.6 | 22.8 | 23.4 | 24.5 |
| Q5_K_S | 20.56 GiB | 21.7 | 21.8 | 22.0 | 22.3 | 22.8 | 23.9 |
| Q4_1 | 18.73 GiB | 19.9 | 20.0 | 20.1 | 20.4 | 21.0 | 22.1 |
| Q4_K_L | 18.38 GiB | 19.6 | 19.7 | 19.8 | 20.1 | 20.6 | 21.8 |
| Q4_K_M | 18.02 GiB | 19.2 | 19.3 | 19.4 | 19.7 | 20.3 | 21.4 |
| Q4_K_S | 17.03 GiB | 18.2 | 18.3 | 18.4 | 18.7 | 19.3 | 20.4 |
| Q4_0 | 16.96 GiB | 18.1 | 18.2 | 18.4 | 18.7 | 19.2 | 20.3 |
| IQ4_NL | 16.94 GiB | 18.1 | 18.2 | 18.4 | 18.6 | 19.2 | 20.3 |
| IQ4_XS | 16.19 GiB | 17.4 | 17.5 | 17.6 | 17.9 | 18.5 | 19.6 |
| Q3_K_L | 15.64 GiB | 16.8 | 16.9 | 17.1 | 17.3 | 17.9 | 19.0 |
| Q3_K_M | 14.43 GiB | 15.6 | 15.7 | 15.8 | 16.1 | 16.7 | 17.8 |
| IQ3_M | 13.39 GiB | 14.6 | 14.7 | 14.8 | 15.1 | 15.7 | 16.8 |
| Q3_K_S | 13.00 GiB | 14.2 | 14.3 | 14.4 | 14.7 | 15.3 | 16.4 |
| IQ3_XS | 12.37 GiB | 13.5 | 13.6 | 13.8 | 14.1 | 14.6 | 15.8 |
| IQ3_XXS | 11.60 GiB | 12.8 | 12.9 | 13.0 | 13.3 | 13.9 | 15.0 |
| Q2_K_L | 11.58 GiB | 12.8 | 12.9 | 13.0 | 13.3 | 13.8 | 15.0 |
| Q2_K | 11.11 GiB | 12.3 | 12.4 | 12.5 | 12.8 | 13.4 | 14.5 |
| IQ2_M | 10.15 GiB | 11.3 | 11.4 | 11.6 | 11.8 | 12.4 | 13.5 |
| IQ2_S | 9.34 GiB | 10.5 | 10.6 | 10.8 | 11.0 | 11.6 | 12.7 |
| IQ2_XS | 8.96 GiB | 10.1 | 10.2 | 10.4 | 10.7 | 11.2 | 12.3 |
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 4,096-token window rather than the full context.