gemma-4-12B-it
4recorded runs
89.7best tok/s
2verified
What the gemma-4-12B-it numbers mean
The fastest verified result on our board is 89.7 output tok/s on an RTX 3060 at Q4_K_XL with a 4096-token context. That is about 11.2 ms per generated token — 500 tokens takes roughly 5.6 seconds. Prompt processing on the same record runs at 114.9 tok/s, so a 2,000-token prompt is read in about 17.4 seconds. Peak VRAM was measured at 9.3 GB. Across the 4 records we hold for this model the range is 37.0–89.7 tok/s on 3 GPUs, because quantisation, context length and the engine build all move the number.
How much VRAM does gemma-4-12B-it need?
gemma-4-12B-it has 12.0B 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) | 8.6 GB | 12 GB |
| Q8_0 (8-bit) | 15.5 GB | 24 GB |
| FP16 (16-bit) | 28.4 GB | 48 GB |
Fastest GPUs for this model (best tok/s)
- RTX 306089.7
- RTX 509088.3
- Radeon AI Pro R970058.2
Models with a similar footprint
| Model | Params | Q4_K_M weights |
|---|---|---|
| gemma-3-12b-it | 12B | 6.8 GB |
| gemma-4-12B-coder-fable5-composer2.5-v1 | 12B | 6.8 GB |
| gemma-4-12B-it-qat | 12B | 6.8 GB |
| NVIDIA-Nemotron-Nano-12B-v2 | 12B | 6.8 GB |
| GLM-4.6V-Flash | 10B | 5.6 GB |
| InternVL3-14B | 14B | 7.9 GB |
| GPU | Model | Quant | Backend | Ctx | tok/s | prompt tok/s | VRAM GB | Source |
|---|---|---|---|---|---|---|---|---|
| RTX 3060 · 12 GB | gemma-4-12B-it | Q4_K_XL | llama.cpp b9775 / be4a6a63e | 4096 | 89.7 ✓ | 114.9 | 9.3 | src |
| RTX 3060 · 12 GB | gemma-4-12B-it | Q4_K_M | llama.cpp b10443 | 32768 | 37.0 ✓ | 892.7 | 7.6 | src |
| RTX 5090 · 32 GB | gemma-4-12B-it | Q8_0 | lmstudio — | 2048 | 88.3 … | 334.8 | — | src |
| Radeon AI Pro R9700 · 32 GB | gemma-4-12B-it | Q4_K_M | llama.cpp — | 2048 | 58.2 … | 2350.8 | — | src |