Coding · Google DeepMind

Gemini 2.5 Pro Nano on HumanEval: score, rank and what it means

Gemini 2.5 Pro Nano scores 71.1 on HumanEval, placing it #387 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
71.1
0–100 scale
Rank
#387
of 600
Percentile
36th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
25.7
points

Score distribution

The chart shows the top 10 models on HumanEval, with Gemini 2.5 Pro Nano highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg 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, Gemini 2.5 Pro Nano sits at #387 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 25.7 points. The median model in this index scores 77.4, which puts Gemini 2.5 Pro Nano below the midpoint.

Google DeepMind models average 82.4 on this benchmark. Gemini 2.5 Pro Nano is 11.3 points below that provider line, so it is a weaker result than the average Google DeepMind model.

Among mid-range models, the average is 71.5. Gemini 2.5 Pro Nano is 0.4 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 71.1 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 $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 HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Arctic Base Snowflake 32768 $2.27 67.5
Grok 3 Nano xAI 8192 $7.12 67.8
Command A Nano Cohere 8192 $5.90 66.3
Reka Flash Mini Reka AI 16384 $5.77 65.5
Gemini 2.5 Pro Nano Google DeepMind 32768 $7.28 69.2
Claude Haiku 4.5 Nano Anthropic 8192 $6.47 68.7
Phi-3.5 Chat Microsoft 16384 $2.64 69.0

Other benchmarks for Gemini 2.5 Pro Nano

BenchmarkScoreRankPercentileRelative
MMLU-Pro 71.4 385 36th
GPQA Diamond 65.4 353 41th
SWE-bench Verified 54.3 390 35th
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 HumanEval?

Gemini 2.5 Pro Nano scores 71.1 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Gemini 2.5 Pro Nano rank on HumanEval?

It ranks #387 of 600 models, in the 36th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Gemini 2.5 Pro Nano 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 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.

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