Model benchmarks
unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF local LLM performance
As of September 2026, unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF runs at up to 95.0 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
4B
Peak speed
95.0 tok/s
Average speed
92.8 tok/s
Avg PP
917.4 tok/s
Min memory
2.0 GB
Max context
524.288 tokens
Avg output / run
8.718 tokens
Avg runtime / run
1m 39s
Avg quality
44.1
Benchmark runs
3
GPUs tested
1
Quality by task
Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task, across all 3 runs. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | 39.7 | 44.1 | 50.3 |
| Agent Workflow | 44.0 | 61.1 | 72.5 |
| Code Generation | 6.8 | 11.8 | 18.4 |
| Role Play & Narrative | 46.1 | 51.5 | 59.3 |
| Research & Analysis | 42.8 | 52.0 | 61.0 |
Performance by hardware and tool
Every hardware/tool/quantization combination unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 4070 | llama.cpp | — | 95.0 tok/s | 92.8 tok/s | 2.0 GB | 524.288 tokens | 44.1 | 3 |
Benchmark runs
All 3 unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF good for coding?
- In our benchmarks, unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF scores 11.8/100 for coding. It runs at about 92.8 tok/s, so if you want more speed, Qwen3.6-35B-A3B-Q4_K_XL is faster (~156.9 tok/s) and still scores well for coding (82.2/100).
- Is unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF good for agentic (tool-using) tasks?
- In our benchmarks, unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF scores 61.1/100 for agentic workflows. It runs at about 92.8 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-Q4_K_S is faster (~165.0 tok/s) and still scores well for agentic workflows (89.3/100).
- How fast is unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF for local inference?
- Across 3 community benchmark runs, unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF reaches up to 95.0 tok/s and averages 92.8 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.
- How much memory does unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF need?
- The leanest observed configuration used about 2.0 GB of memory.
- Which tools have been used to run unsloth/NVIDIA-Nemotron-3-Nano-4B-GGUF?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.