Coding · NVIDIA

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

Nemotron Nano scores 54.1 on SWE-bench Verified, placing it #392 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
54.1
0–100 scale
Rank
#392
of 600
Percentile
35th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
27.6
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Nemotron Nano 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 sits at #392 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 27.6 points. The median model in this index scores 61.0, which puts Nemotron Nano below the midpoint.

NVIDIA models average 48.4 on this benchmark. Nemotron Nano is 5.7 points above that provider line, so it is a stronger result than the average NVIDIA model.

Among open-weight models, the average is 55.5. Nemotron Nano is 1.4 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 54.1 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 $2.24 per million input tokens, Nemotron Nano 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
Nemotron Nano Instruct NVIDIA 32768 $2.33 67.4
StableLM 2 Instruct Stability AI 16384 $1.93 65.2
Gemini 2.5 Pro Nano Google DeepMind 32768 $7.28 69.2
Arctic Snowflake 8192 $2.72 68.8
Nemotron Nano NVIDIA 8192 $2.24 66.6
Nemotron Nano Chat NVIDIA 32768 $2.21 66.2
DeepSeek-R1 8B DeepSeek 16384 $1.87 64.3

Other benchmarks for Nemotron Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 70.5 393 35th
GPQA Diamond 65.1 357 41th
HumanEval 69.7 399 34th
MATH-500 68.4 395 34th
AIME 2025 60.2 387 36th
LiveCodeBench 58.3 385 36th
IFEval 74.2 402 33th
TruthfulQA 68.8 406 32th
HellaSwag 78.0 402 33th
MMMU 64.8 383 36th
Arena Elo 1334.4 382 36th

FAQ

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

Nemotron Nano scores 54.1 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Nemotron Nano rank on SWE-bench Verified?

It ranks #392 of 600 models, in the 35th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Nemotron Nano 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 cost?

Nemotron Nano costs $2.24 per million input tokens and $8.55 per million output tokens.

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