Coding · NVIDIA

Nemotron Nano 7B on SWE-bench Verified: score, rank and what it means

Nemotron Nano 7B scores 31.0 on SWE-bench Verified, placing it #576 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
31.0
0–100 scale
Rank
#576
of 600
Percentile
4th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
50.7
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Nemotron Nano 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Nemotron Nano 7B sits at #576 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 50.7 points. The median model in this index scores 61.0, which puts Nemotron Nano 7B below the midpoint.

NVIDIA models average 48.4 on this benchmark. Nemotron Nano 7B is 17.4 points below that provider line, so it is a weaker result than the average NVIDIA model.

Among small open-weight models, the average is 39.0. Nemotron Nano 7B is 8.0 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 31.0 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 $0.35 per million input tokens, Nemotron Nano 7B is below the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
DBRX 1.5B Databricks 16384 $0.32 47.0
Gemma 3 1.5B Google DeepMind 32768 $0.40 48.9
Molmo 7B Allen Institute for AI 32768 $0.42 49.3
Nemotron Nano 8B NVIDIA 8192 $0.46 48.1
Nemotron Nano 7B NVIDIA 8192 $0.35 47.5
StableLM 2 8B Stability AI 32768 $0.38 47.0
StableLM 2 7B Stability AI 8192 $0.28 44.3

Other benchmarks for Nemotron Nano 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 56.9 561 7th
GPQA Diamond 41.7 580 3th
HumanEval 49.5 576 4th
MATH-500 48.7 570 5th
AIME 2025 31.3 580 3th
LiveCodeBench 32.3 579 4th
IFEval 60.7 569 5th
TruthfulQA 56.6 558 7th
HellaSwag 67.6 560 7th
MMMU 46.7 575 4th
Arena Elo 1180.8 575 4th

FAQ

What score does Nemotron Nano 7B get on SWE-bench Verified?

Nemotron Nano 7B scores 31.0 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Nemotron Nano 7B rank on SWE-bench Verified?

It ranks #576 of 600 models, in the 4th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Nemotron Nano 7B good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified 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 7B cost?

Nemotron Nano 7B costs $0.35 per million input tokens and $1.30 per million output tokens.

Related