Models › gemma-4-31B-it
gemma-4-31B-it: VRAM needs and speed by GPU
At Q4_K_M, gemma-4-31B-it needs about 19.9 GB of VRAM. No measured runs yet. Speeds below are estimates. Submit a run.
30.7B parameters · license: apache-2.0 · 262,144-token context · GGUF published Apr 1, 2026 · GGUF files on Hugging Face
Memory needed per quantization
| Quant | File size | Needs (estimate) | Smallest card it fits |
|---|---|---|---|
| UD-IQ2_XXS | 8.5 GB | 10.1 GB | 12 GB cards |
| UD-IQ2_M | 10.8 GB | 12.3 GB | 16 GB cards |
| UD-Q2_K_XL | 11.8 GB | 13.3 GB | 16 GB cards |
| UD-IQ3_XXS | 11.8 GB | 13.4 GB | 16 GB cards |
| Q3_K_S | 13.2 GB | 14.8 GB | 16 GB cards |
| Q3_K_M | 14.7 GB | 16.3 GB | 24 GB cards |
| UD-Q3_K_XL | 15.4 GB | 17.0 GB | 24 GB cards |
| IQ4_XS | 16.4 GB | 17.9 GB | 24 GB cards |
| IQ4_NL | 17.3 GB | 18.9 GB | 24 GB cards |
| Q4_0 | 17.3 GB | 18.9 GB | 24 GB cards |
| Q4_K_S | 17.4 GB | 19.0 GB | 24 GB cards |
| Q4_K_M | 18.3 GB | 19.9 GB | 24 GB cards |
| UD-Q4_K_XL | 18.8 GB | 20.4 GB | 24 GB cards |
| Q4_1 | 19.1 GB | 20.7 GB | 24 GB cards |
| Q5_K_S | 21.1 GB | 22.7 GB | 24 GB cards |
| Q5_K_M | 21.7 GB | 23.2 GB | 24 GB cards |
| UD-Q5_K_XL | 21.9 GB | 23.5 GB | 24 GB cards |
| Q6_K | 25.2 GB | 26.8 GB | 32 GB cards |
| UD-Q6_K_XL | 27.5 GB | 29.1 GB | 32 GB cards |
| Q8_0 | 32.6 GB | 34.2 GB | 48 GB cards |
| UD-Q8_K_XL | 35.0 GB | 36.6 GB | 48 GB cards |
| BF16 | 61.4 GB | 63.0 GB | 96 GB cards |
Expected speed on popular hardware
| Hardware | Best quant that fits | Expected tok/s |
|---|---|---|
| NVIDIA RTX 3060 | UD-IQ2_XXS | 36.1 estimate |
| NVIDIA RTX 4060 Ti | Does not fit | |
| NVIDIA RTX 3090 | Q5_K_M | 30.3 estimate |
| NVIDIA RTX 4090 | Q5_K_M | 33.6 estimate |
| NVIDIA RTX 5090 | Q6_K | 45.6 estimate |
| AMD Radeon RX 7900 XTX | Q5_K_M | 33.7 estimate |
| Apple M4 Pro (20-core GPU) (64 GB) | Q8_0 | 7.1 estimate |
| Apple M3 Max (40-core GPU) (64 GB) | Q8_0 | 10.4 estimate |
| AMD Ryzen AI Max+ 395 (Radeon 8060S) | Q8_0 | 6.4 estimate |
Too big for your card?
Run gemma-4-31B-it on a rented 24-80 GB GPU by the hour.
Rent a bigger GPU on RunPodAffiliate link: if you sign up, RigBench may earn a referral credit. It never affects rankings or numbers.