gemma-4-31B-it
4recorded runs
28.3best tok/s
3verified
What the gemma-4-31B-it numbers mean
The fastest verified result on our board is 28.3 output tok/s on an CMP 170HX at NVFP4 with a 32768-token context. That is about 35.4 ms per generated token — 500 tokens takes roughly 17.7 seconds. Prompt processing on the same record runs at 967.9 tok/s, so a 2,000-token prompt is read in about 2.1 seconds. Peak VRAM was measured at 58.7 GB. Across the 4 records we hold for this model the range is 15.8–28.3 tok/s on 4 GPUs, because quantisation, context length and the engine build all move the number.
How much VRAM does gemma-4-31B-it need?
gemma-4-31B-it has 33.0B parameters. These estimates use the same formula as the VRAM calculator: weights, plus about 15% for a moderate-context KV cache and runtime overhead, plus a small engine floor.
| Quantisation | Estimated VRAM | Smallest card that fits |
|---|---|---|
| Q4_K_M (4-bit) | 22.1 GB | 32 GB |
| Q8_0 (8-bit) | 41.1 GB | 64 GB |
| FP16 (16-bit) | 76.7 GB | 96 GB |
Fastest GPUs for this model (best tok/s)
- CMP 170HX28.3
- Radeon AI Pro R970025.4
- Radeon AI Pro R9700 x323.9
- RTX 3060 x215.8
Models with a similar footprint
| Model | Params | Q4_K_M weights |
|---|---|---|
| GLM-Z1-32B-0414 | 33B | 18.6 GB |
| Laguna-XS-2.1 | 33B | 18.6 GB |
| Nemotron-Cascade-2-30B-A3B | 32B | 18.0 GB |
| NVIDIA-Nemotron-3-Nano-30B-A3B | 32B | 18.0 GB |
| NVIDIA-Nemotron-3.5-Lightning-30B-A3B | 32B | 18.0 GB |
| Olmo-3-32B-Think | 32B | 18.0 GB |
| GPU | Model | Quant | Backend | Ctx | tok/s | prompt tok/s | VRAM GB | Source |
|---|---|---|---|---|---|---|---|---|
| CMP 170HX · 64 GB | gemma-4-31B-it | NVFP4 | vllm 0.28.0 | 32768 | 28.3 ✓ | 967.9 | 58.7 | src |
| Radeon AI Pro R9700 x3 · 32 GB | gemma-4-31B-it | Q8_0 | llama.cpp b10434 | 794 | 23.9 ✓ | 597.3 | — | src |
| RTX 3060 x2 · 12 GB | gemma-4-31B-it | Q4_K_M | llama.cpp b10443 | 65536 | 15.8 ✓ | 578.2 | 21.7 | src |
| Radeon AI Pro R9700 · 32 GB | gemma-4-31B-it | Q4_K_XL | llama.cpp — | 2048 | 25.4 … | 923.1 | — | src |