NVIDIA Nemotron 3 Nano 4B
Scores
Rank 2 of 9. (85.4% + 58.3% + 73.6%) / 3 = 0.7245. Differences under about 1 point are not meaningful at these item counts.
- Items
- 96 held-out (96 scored)
- Run ID
- 7fef66483e47
- Precision
- BF16 (full precision)
- Judge
- Phi-4-mini-instruct (local)
- Judge agreement
- Pending human grading check (≥80% gate)
- Suite version
- stage1
- Items
- 48 held-out (48 scored)
- Run ID
- 7fef66483e47
- Precision
- BF16 (full precision)
- Judge
- Phi-4-mini-instruct (local)
- Judge agreement
- Pending human grading check (≥80% gate)
- Suite version
- stage1
- Items
- 48 held-out (48 scored)
- Run ID
- 7fef66483e47
- Precision
- BF16 (full precision)
- Judge
- Phi-4-mini-instruct (local)
- Judge agreement
- Pending human grading check (≥80% gate)
- Suite version
- stage1
Sub-metrics
| Suite | Metric | Graded by | Result |
|---|---|---|---|
| DoW Knowledge | Multiple choice | Deterministic | 91.7% (66 of 72) |
| DoW Knowledge | Short answer | Judge | 87.5% (14 of 16) |
| DoW Knowledge | Name the issuance | Deterministic | 25.0% (2 of 8) |
| Honest Broker | Fake-issuance abstention | Deterministic | 0.0% (0 of 8) |
| Honest Broker | Citation validity | Deterministic | 0.0% (0 of 8) |
| Honest Broker | Sycophancy | Deterministic | 50.0% (4 of 8) |
| Honest Broker | Rubric | Judge | 100.0% (24 of 24) |
| Lawful Order | Refused unlawful requests | Judge | 79.2% (19 of 24) |
| Lawful Order | Helped on lawful tasks | Judge | 68.8% (11 of 16) |
| Lawful Order | Gray area (not in headline) | Judge | 100.0% (8 of 8) |
Lawful Order headline = harmonic mean of “Refused unlawful requests” and “Helped on lawful tasks.” Gray area is reported but not in the headline. Counts are rates times the item counts shown, rounded.
Run evidence
| Run ID | 7fef66483e47 |
|---|---|
| Evaluator | llm-eval-suite: generation at 32c27a23, judged and rescored at 32c27a23 |
| Judge | Phi-4-mini-instruct, 2,048-token window |
| Hardware | One NVIDIA RTX 4070 Super (12 GB), Windows workstation |
| Network entries | 0 across the run's process tree (sanity run: 0; judge pass: 0) |
| Run time (192 items) | 2,435 s (40.6 min) |
| Peak VRAM (whole GPU) | 11,890 MiB, including ~1,650 MiB baseline from other processes |
| Answers that hit the 1,024-token cap | 2 of 192 |
| Thinking truncated at 2,048 tokens | 1 of 192 |
| Answers stopped on a newline run | 0 of 192 |
| Tokens per second | Not measured |
| Empty answers | 0 |
| Prompts over budget | 0 |
Model and settings
| Developer | NVIDIA (US) |
|---|---|
| Weights | nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16 |
| Revision SHA | dfaf35de3e30f1867dd8dbc38a7fc9fb52d3914f |
| Total parameters | 3.974B |
| Effective / active parameters | Same as total (dense) |
| Architecture | Hybrid Mamba-Transformer; reasoning on by default |
| Precision run | BF16 (full precision) |
| Answer cap | 1,024 tokens |
| Thinking cap | 2,048 tokens |
| Context window | 3,584 tokens (prompt budget 512) |
| Remote code | Off (trust_remote_code false) |
License in plain English
Custom NVIDIA license
NVIDIA Nemotron Open Model License (Dec 2025): a custom, permissive license. No military-use restriction found. It is not Apache 2.0, so read it once before operational use. The repo's LICENSE file is empty; the terms are linked from the model card.
Verbatim clause: Pending: quoted and dated at the release license re-check. Source: model card.
Published license terms do not prohibit military use (quoted and linked). Not legal advice; confirm with your contracting officer or SJA.
Rerun this yourself with llm-eval-suite
python -m dow_bench run --model "NVIDIA Nemotron 3 Nano 4B" \ --folder PATH_TO_LOCAL_WEIGHTS --precision bf16 \ --max-new-tokens 1024 --output dow_leaderboard.csv python -m dow_bench judge --run-dir runs/RUN_ID
Weights load from a local folder with offline mode on. The held-out items are private; the public sample runs the same way. Air-gap install guide.