Coding · Google DeepMind

Gemini 2.5 Pro Nano on SWE-bench Verified: score, rank and what it means

Gemini 2.5 Pro Nano scores 54.3 on SWE-bench Verified, placing it #390 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
54.3
0–100 scale
Rank
#390
of 600
Percentile
35th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
27.4
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Gemini 2.5 Pro 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, Gemini 2.5 Pro Nano sits at #390 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 27.4 points. The median model in this index scores 61.0, which puts Gemini 2.5 Pro Nano below the midpoint.

Google DeepMind models average 66.4 on this benchmark. Gemini 2.5 Pro Nano is 12.1 points below that provider line, so it is a weaker result than the average Google DeepMind model.

Among mid-range models, the average is 54.9. Gemini 2.5 Pro Nano is 0.6 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 54.3 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 $7.28 per million input tokens, Gemini 2.5 Pro 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 Groq Base Groq 32768 $2.66 68.4
Command A Nano Cohere 8192 $5.90 66.3
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

Other benchmarks for Gemini 2.5 Pro Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 71.4 385 36th
GPQA Diamond 65.4 353 41th
HumanEval 71.1 387 36th
MATH-500 74.9 327 46th
AIME 2025 63.7 360 40th
LiveCodeBench 59.2 376 37th
IFEval 79.9 334 44th
TruthfulQA 74.4 343 43th
HellaSwag 80.7 375 38th
MMMU 65.9 374 38th
Arena Elo 1349.7 364 39th

FAQ

What score does Gemini 2.5 Pro Nano get on SWE-bench Verified?

Gemini 2.5 Pro Nano scores 54.3 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Gemini 2.5 Pro Nano rank on SWE-bench Verified?

It ranks #390 of 600 models, in the 35th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Gemini 2.5 Pro 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 Gemini 2.5 Pro Nano cost?

Gemini 2.5 Pro Nano costs $7.28 per million input tokens and $28.44 per million output tokens.

Related