Nemotron Nano Instruct on HumanEval: score, rank and what it means
Nemotron Nano Instruct scores 72.9 on HumanEval, placing it #375 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.
Score distribution
The chart shows the top 10 models on HumanEval, with Nemotron Nano Instruct highlighted. Longer bars mean higher scores.
Top 10 leaderboard
| # | Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|---|
| 1 | GPT-5.2 Pro | OpenAI | 2000000 | $21.32 | 89.6 |
| 2 | Gemini 3 Pro Pro | Google DeepMind | 200000 | $19.80 | 87.3 |
| 3 | o4 Max | OpenAI | 2000000 | $19.51 | 86.2 |
| 4 | Grok 4 Reasoning | xAI | 2000000 | $19.67 | 87.8 |
| 5 | Claude Opus 4.5 | Anthropic | 400000 | $19.42 | 87.7 |
| 6 | GPT-5.2 Max | OpenAI | 1000000 | $21.39 | 89.2 |
| 7 | Claude Opus 4.5 Pro | Anthropic | 200000 | $20.98 | 89.1 |
| 8 | Grok 4 Max | xAI | 2000000 | $19.70 | 86.6 |
| 9 | GPT-5.2 Turbo | OpenAI | 1000000 | $20.73 | 87.4 |
| 10 | GPT-5.1 Reasoning | OpenAI | 400000 | $20.27 | 88.3 |
What this score means
On HumanEval, Nemotron Nano Instruct sits at #375 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 23.9 points. The median model in this index scores 77.4, which puts Nemotron Nano Instruct below the midpoint.
NVIDIA models average 65.9 on this benchmark. Nemotron Nano Instruct is 7.0 points above that provider line, so it is a stronger result than the average NVIDIA model.
Among open-weight models, the average is 72.4. Nemotron Nano Instruct is 0.5 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.
Read a 72.9 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.
Price context
At $2.33 per million input tokens, Nemotron Nano Instruct is below the median input price of $4.00 across the 600 models scored on HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Phi-3.5 Base | Microsoft | 65536 | $2.24 | 66.6 |
| Gemini 3 Flash Nano | Google DeepMind | 32768 | $7.56 | 69.4 |
| Firesearch Max | Fireworks AI | 8192 | $7.80 | 69.9 |
| Mixtral Turbo Base | Together AI | 32768 | $2.53 | 69.7 |
| Nemotron Nano Instruct | NVIDIA | 32768 | $2.33 | 67.4 |
| Claude 3.7 Sonnet Nano | Anthropic | 65536 | $6.93 | 68.9 |
| o3 Nano | OpenAI | 32768 | $7.78 | 70.6 |
Other benchmarks for Nemotron Nano Instruct
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 72.6 | 371 | 38th | |
| GPQA Diamond | 64.7 | 366 | 39th | |
| SWE-bench Verified | 54.5 | 388 | 35th | |
| MATH-500 | 67.4 | 404 | 33th | |
| AIME 2025 | 58.6 | 396 | 34th | |
| LiveCodeBench | 57.1 | 395 | 34th | |
| IFEval | 75.2 | 396 | 34th | |
| TruthfulQA | 73.0 | 369 | 39th | |
| HellaSwag | 79.7 | 384 | 36th | |
| MMMU | 66.2 | 368 | 39th | |
| Arena Elo | 1331.2 | 387 | 36th |
FAQ
What score does Nemotron Nano Instruct get on HumanEval?
Nemotron Nano Instruct scores 72.9 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.
How does Nemotron Nano Instruct rank on HumanEval?
It ranks #375 of 600 models, in the 38th percentile. The leader is GPT-5.2 Pro at 96.8.
Is Nemotron Nano Instruct good at HumanEval?
It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.
How is the HumanEval score calculated?
HumanEval is a coding benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.
What does Nemotron Nano Instruct cost?
Nemotron Nano Instruct costs $2.33 per million input tokens and $11.92 per million output tokens.