gemma-3n-E4B-it-text
1recorded run
135.4best tok/s
0verified
What the gemma-3n-E4B-it-text numbers mean
The fastest result on our board is 135.4 output tok/s on an RTX 5090 at Q8_0 with a 2048-token context. That is about 7.4 ms per generated token — 500 tokens takes roughly 3.7 seconds. Prompt processing on the same record runs at 545.5 tok/s, so a 2,000-token prompt is read in about 3.7 seconds.
How much VRAM does gemma-3n-E4B-it-text need?
gemma-3n-E4B-it-text has 4.0B 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) | 3.4 GB | 8 GB |
| Q8_0 (8-bit) | 5.7 GB | 8 GB |
| FP16 (16-bit) | 10.0 GB | 12 GB |
Fastest GPUs for this model (best tok/s)
- RTX 5090135.4
Models with a similar footprint
| Model | Params | Q4_K_M weights |
|---|---|---|
| NVIDIA-Nemotron-3-Nano-4B | 4B | 2.2 GB |
| Phi-4-mini-reasoning | 4B | 2.2 GB |
| Qwen3-4B | 4B | 2.2 GB |
| Qwen3-4B-Thinking-2507 | 4B | 2.2 GB |
| Qwen3.5-4B | 4B | 2.2 GB |
| Qwen3.5-4B-MTP | 4B | 2.2 GB |