Coding · OpenAI

o3 Nano on SWE-bench Verified: score, rank and what it means

o3 Nano scores 57.9 on SWE-bench Verified, placing it #358 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
57.9
0–100 scale
Rank
#358
of 600
Percentile
40th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
23.8
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with o3 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, o3 Nano sits at #358 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 23.8 points. The median model in this index scores 61.0, which puts o3 Nano below the midpoint.

OpenAI models average 72.7 on this benchmark. o3 Nano is 14.8 points below that provider line, so it is a weaker result than the average OpenAI model.

Among mid-range models, the average is 54.9. o3 Nano is 3.0 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 57.9 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 $7.78 per million input tokens, o3 Nano is above 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
Mixtral Turbo Chat Together AI 32768 $3.02 71.7
Auto OpenRouter 32768 $7.53 70.2
Mixtral Turbo Base Together AI 32768 $2.53 69.7
Molmo Allen Institute for AI 32768 $2.49 68.5
o3 Nano OpenAI 32768 $7.78 70.6
Mixtral Groq Instruct Groq 16384 $3.25 72.5
Mixtral Turbo Together AI 65536 $3.20 72.4

Other benchmarks for o3 Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.3 325 46th
GPQA Diamond 64.8 364 39th
HumanEval 72.5 377 37th
MATH-500 74.5 339 44th
AIME 2025 65.6 334 44th
LiveCodeBench 60.3 365 39th
IFEval 78.2 365 39th
TruthfulQA 75.4 324 46th
HellaSwag 81.4 360 40th
MMMU 70.2 295 51th
Arena Elo 1354.5 355 41th

FAQ

What score does o3 Nano get on SWE-bench Verified?

o3 Nano scores 57.9 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does o3 Nano rank on SWE-bench Verified?

It ranks #358 of 600 models, in the 40th percentile. The leader is GPT-5.2 Pro at 81.7.

Is o3 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 o3 Nano cost?

o3 Nano costs $7.78 per million input tokens and $29.81 per million output tokens.

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