NVIDIA-Nemotron-3-Nano-4B
3recorded runs
237.8best tok/s
1verified
What the NVIDIA-Nemotron-3-Nano-4B numbers mean
The fastest verified result on our board is 185.8 output tok/s on an RTX 5070 at Q4_K_M with a 32768-token context. That is about 5.4 ms per generated token — 500 tokens takes roughly 2.7 seconds. Prompt processing on the same record runs at 5377.5 tok/s, so a 2,000-token prompt is read in about 0.4 seconds. Peak VRAM was measured at 4.2 GB. Across the 3 records we hold for this model the range is 171.3–237.8 tok/s on 3 GPUs, because quantisation, context length and the engine build all move the number.
How much VRAM does NVIDIA-Nemotron-3-Nano-4B need?
NVIDIA-Nemotron-3-Nano-4B 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 |
Models with a similar footprint
| Model | Params | Q4_K_M weights |
|---|---|---|
| gemma-3n-E4B-it-text | 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 |
| GPU | Model | Quant | Backend | Ctx | tok/s | prompt tok/s | VRAM GB | Source |
|---|---|---|---|---|---|---|---|---|
| RTX 5070 · 12 GB | NVIDIA-Nemotron-3-Nano-4B | Q4_K_M | llama.cpp b10449 (0d9ceae1e38291035605613ab41a… | 32768 | 185.8 ✓ | 5377.5 | 4.2 | src |
| RTX 5090 · 32 GB | NVIDIA-Nemotron-3-Nano-4B | Q8_0 | lmstudio — | 2048 | 237.8 … | 1173.5 | — | src |
| RTX 3090 · 24 GB | NVIDIA-Nemotron-3-Nano-4B | Q4_K_M | llama.cpp — | 512 | 171.3 … | 5608.8 | 0.0 | src |