Does DeepSeek-V3-0324 fit in 12GB of VRAM?
Not at these settings. No indexed quantization of DeepSeek-V3-0324 fits 12GB card at any context we compute, with q8_0 KV. The smallest shipped quantization is 124.38 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 | 1250.09 GiB | 1251.1 | 1251.3 | 1251.5 | 1252.1 | 1253.2 | 1255.5 |
| Q8_0 | 664.30 GiB | 665.3 | 665.5 | 665.7 | 666.3 | 667.5 | 669.7 |
| Q6_K | 513.09 GiB | 514.1 | 514.3 | 514.5 | 515.1 | 516.2 | 518.5 |
| Q5_K_M | 442.93 GiB | 443.9 | 444.1 | 444.4 | 444.9 | 446.1 | 448.4 |
| Q5_K_S | 430.10 GiB | 431.1 | 431.3 | 431.5 | 432.1 | 433.3 | 435.5 |
| Q4_1 | 391.10 GiB | 392.1 | 392.3 | 392.5 | 393.1 | 394.3 | 396.5 |
| Q4_K_M | 376.89 GiB | 377.9 | 378.1 | 378.3 | 378.9 | 380.1 | 382.3 |
| Q4_K_S | 353.90 GiB | 354.9 | 355.1 | 355.4 | 355.9 | 357.1 | 359.3 |
| Q4_0 | 353.00 GiB | 354.0 | 354.2 | 354.5 | 355.0 | 356.2 | 358.4 |
| IQ4_NL | 352.34 GiB | 353.4 | 353.5 | 353.8 | 354.4 | 355.5 | 357.8 |
| IQ4_XS | 332.90 GiB | 333.9 | 334.1 | 334.3 | 334.9 | 336.1 | 338.3 |
| Q3_K_M | 297.58 GiB | 298.6 | 298.7 | 299.0 | 299.6 | 300.7 | 303.0 |
| UD-IQ3_XXS | 254.55 GiB | 255.6 | 255.7 | 256.0 | 256.6 | 257.7 | 260.0 |
| IQ3_XXS | 240.22 GiB | 241.2 | 241.4 | 241.7 | 242.2 | 243.4 | 245.7 |
| Q2_K_L | 228.11 GiB | 229.1 | 229.3 | 229.6 | 230.1 | 231.3 | 233.5 |
| Q2_K | 227.62 GiB | 228.6 | 228.8 | 229.1 | 229.6 | 230.8 | 233.1 |
| UD-IQ2_M | 212.09 GiB | 213.1 | 213.3 | 213.5 | 214.1 | 215.2 | 217.5 |
| UD-IQ2_XXS | 203.64 GiB | 204.7 | 204.8 | 205.1 | 205.7 | 206.8 | 209.1 |
| IQ2_M | 202.50 GiB | 203.5 | 203.7 | 203.9 | 204.5 | 205.7 | 207.9 |
| UD-IQ1_M | 186.94 GiB | 188.0 | 188.1 | 188.4 | 189.0 | 190.1 | 192.4 |
| IQ2_S | 183.47 GiB | 184.5 | 184.6 | 184.9 | 185.5 | 186.6 | 188.9 |
| UD-IQ1_S | 173.45 GiB | 174.5 | 174.6 | 174.9 | 175.5 | 176.6 | 178.9 |
| IQ2_XXS | 162.45 GiB | 163.5 | 163.6 | 163.9 | 164.5 | 165.6 | 167.9 |
| IQ1_M | 138.66 GiB | 139.7 | 139.8 | 140.1 | 140.7 | 141.8 | 144.1 |
| IQ1_S | 124.38 GiB | 125.4 | 125.5 | 125.8 | 126.4 | 127.5 | 129.8 |
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 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, this model uses latent attention and allocates no V cache at all, so any formula reading num_key_value_heads overstates its cache by more than an order of magnitude.