Does GLM-5 fit in 24GB of VRAM?
Not at these settings. No indexed quantization of GLM-5 fits 24GB card at any context we compute, with q8_0 KV. The smallest shipped quantization is 164.05 GiB in weights alone, against 22.32 GiB usable. CPU offload can still run it, slowly.
Every quantization at every context
| Quant | Weights● | 4K◐ | 8K◐ | 16K◐ | 32K◐ | 64K◐ | 128K◐ |
|---|---|---|---|---|---|---|---|
| BF16 | 1404.42 GiB | 1405.4 | 1405.6 | 1406.0 | 1406.7 | 1408.2 | 1411.1 |
| Q8_0 | 746.31 GiB | 747.3 | 747.5 | 747.9 | 748.6 | 750.1 | 753.0 |
| Q6_K | 576.84 GiB | 577.9 | 578.1 | 578.4 | 579.1 | 580.6 | 583.5 |
| Q5_K_M | 498.42 GiB | 499.4 | 499.6 | 500.0 | 500.7 | 502.2 | 505.1 |
| Q5_K_S | 484.04 GiB | 485.1 | 485.3 | 485.6 | 486.3 | 487.8 | 490.7 |
| Q4_1 | 440.24 GiB | 441.3 | 441.5 | 441.8 | 442.5 | 444.0 | 446.9 |
| Q4_K_M | 424.57 GiB | 425.6 | 425.8 | 426.1 | 426.9 | 428.3 | 431.2 |
| Q4_K_S | 398.95 GiB | 400.0 | 400.2 | 400.5 | 401.3 | 402.7 | 405.6 |
| Q4_0 | 397.81 GiB | 398.8 | 399.0 | 399.4 | 400.1 | 401.6 | 404.5 |
| IQ4_NL | 396.67 GiB | 397.7 | 397.9 | 398.2 | 399.0 | 400.4 | 403.3 |
| IQ4_XS | 375.23 GiB | 376.3 | 376.4 | 376.8 | 377.5 | 379.0 | 381.9 |
| Q3_K_M | 335.56 GiB | 336.6 | 336.8 | 337.1 | 337.9 | 339.3 | 342.2 |
| Q3_K_S | 303.87 GiB | 304.9 | 305.1 | 305.4 | 306.2 | 307.6 | 310.5 |
| UD-IQ3_XXS | 283.62 GiB | 284.7 | 284.8 | 285.2 | 285.9 | 287.4 | 290.3 |
| Q2_K_L | 257.21 GiB | 258.2 | 258.4 | 258.8 | 259.5 | 261.0 | 263.9 |
| Q2_K | 257.00 GiB | 258.0 | 258.2 | 258.6 | 259.3 | 260.8 | 263.7 |
| UD-IQ2_M | 237.27 GiB | 238.3 | 238.5 | 238.8 | 239.6 | 241.0 | 243.9 |
| UD-IQ2_XXS | 224.52 GiB | 225.5 | 225.7 | 226.1 | 226.8 | 228.3 | 231.2 |
| UD-IQ1_M | 208.48 GiB | 209.5 | 209.7 | 210.1 | 210.8 | 212.2 | 215.2 |
| UD-IQ1_S | 189.71 GiB | 190.7 | 190.9 | 191.3 | 192.0 | 193.5 | 196.4 |
| UD-TQ1_0 | 164.05 GiB | 165.1 | 165.3 | 165.6 | 166.4 | 167.8 | 170.7 |
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 24GB 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.