Commonsense · Google DeepMind

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

Gemini 2.5 Pro scores 89.7 on HellaSwag, placing it #94 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
89.7
0–100 scale
Rank
#94
of 600
Percentile
84th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
6.4
points

Score distribution

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

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, Gemini 2.5 Pro sits at #94 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 6.4 points. The median model in this index scores 83.6, which puts Gemini 2.5 Pro above the midpoint.

Google DeepMind models average 86.9 on this benchmark. Gemini 2.5 Pro is 2.8 points above that provider line, so it is a stronger result than the average Google DeepMind model.

Among multimodal models, the average is 86.8. Gemini 2.5 Pro is 2.9 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 89.7 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 $15.20 per million input tokens, Gemini 2.5 Pro is above the median input price of $4.00 across the 600 models scored on HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
DeepSeek-R1 DeepSeek 128000 $5.83 82.8
Gemini 3 Flash Google DeepMind 128000 $15.67 83.6
Claude 3.7 Sonnet Pro Anthropic 128000 $16.07 83.3
GPT-4.1 Vision OpenAI 1000000 $14.88 82.0
Gemini 2.5 Pro Google DeepMind 200000 $15.20 81.6
Grok 3 Reasoning xAI 200000 $16.07 82.9
o3 Vision OpenAI 1000000 $15.24 81.8

Other benchmarks for Gemini 2.5 Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 83.6 91 85th
GPQA Diamond 76.5 109 82th
SWE-bench Verified 70.2 104 83th
HumanEval 87.7 76 87th
MATH-500 86.8 83 86th
AIME 2025 76.1 139 77th
LiveCodeBench 76.2 81 87th
IFEval 87.6 111 82th
TruthfulQA 82.8 110 82th
MMMU 80.5 52 91th
Arena Elo 1455.0 63 90th

FAQ

What score does Gemini 2.5 Pro get on HellaSwag?

Gemini 2.5 Pro scores 89.7 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does Gemini 2.5 Pro rank on HellaSwag?

It ranks #94 of 600 models, in the 84th percentile. The leader is GPT-5.2 Max at 96.1.

Is Gemini 2.5 Pro good at HellaSwag?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the HellaSwag score calculated?

HellaSwag is a commonsense 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 cost?

Gemini 2.5 Pro costs $15.20 per million input tokens and $57.83 per million output tokens.

Related