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Gemini 2.5 Pro

by Google DeepMind · Released Jun 2025

Multimodal1M Context
58.7
avg score
Rank #96
Compare
Better than 69% of all models
Context
1.0M tokens (~524 books)
Input $/1M
$1.25
Output $/1M
$10.00
Type
multimodal
License
Proprietary
Benchmarks
50 tested
Data as of
About

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs “thinking” capabilities, enabling it to reason through responses with enhanced accuracy...

Tested on 50 benchmarks · BenchGecko score 58.7. Top scores: Chatbot Arena Elo — Overall (1445.6%), Chatbot Arena Elo — Coding (1227.0%), MATH level 5 (95.6%).

Looking for similar performance at lower cost?
DeepSeek V4.1 Flash scores 58.7 (100% as good) at $0.15/1M input · 88% cheaper
Capabilities
coding
52.4
#80 globally
reasoning
46.6
#85 globally
math
44.2
#140 globally
knowledge
57.6
#75 globally
agentic
18.4
#47 globally
general
38.2
#77 globally
speed
30.5
#84 globally
language
87.0
#28 globally
Benchmark Scores
Compare All
Tested on 50 benchmarks · Ranked across 9 categories
Score Distribution (all 312 models)
0255075100
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Aider polyglot

Multi-language code editing from Aider. Tests editing ability across Python, JavaScript, TypeScript, Java, C++, Go, Rust, and more.

83.1·
OpenCompass — LiveCodeBenchV6

OpenCompass Live Code Bench v6. Fresh competitive programming problems to evaluate code generation without memorization.

71.3·
CadEval

Computer-aided design evaluation. Tests understanding of CAD concepts, 3D modeling, and engineering design principles.

64.0·
HELM — WildBench

Stanford HELM WildBench evaluation. Tests reasoning on challenging real-world tasks.

85.7·
SimpleBench

Deceptively simple questions that humans find easy but AI models often get wrong. Tests common sense and reasoning gaps.

54.9·
ARC-AGI

Abstraction and Reasoning Corpus. Tests fluid intelligence through novel visual pattern recognition puzzles. Core measure of general intelligence.

41.0·
MATH level 5

Competition-level math from AMC, AIME, and olympiad problems. Level 5 is the hardest tier, requiring creative problem-solving.

95.6·
OpenCompass — AIME2025

OpenCompass evaluation on AIME 2025 problems. Tests mathematical reasoning on fresh competition problems.

88.7·
OTIS Mock AIME 2024-2025

Mock AIME (American Invitational Mathematics Exam) problems from OTIS. Tests mathematical competition performance.

84.7·
Excellent (85+) Good (70-85) Average (50-70) Below (<50)
Links
Documentation
BenchGecko API
gemini-2-5-pro
Specifications
  • Typemultimodal
  • Context1.0M tokens (~524 books)
  • ReleasedJun 2025
  • LicenseProprietary
  • StatusActive
  • Cost / Message~$0.013
Available On
Google DeepMind logoGoogle DeepMind$1.25
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Gemini 2.5 Pro is a proprietary multimodal AI model by Google DeepMind, released in June 2025. It has an average benchmark score of 58.7. Context window: 1M tokens.

Key facts · as of 2026-10-05

  • Gemini 2.5 Pro by Google DeepMind. BenchGecko score 58.7, rank 94 of 312 scored models (normalized average of public benchmark scores).
  • List price $1.25 input · $10.00 output per 1M tokens (as of 2026-10-05).
  • Sold by 7 providers (as of 2026-10-05): Google AI Studio $0.63 in / $5.00 out · Google $1.25 in / $10.00 out · Google $1.25 in / $10.00 out · Google $1.25 in / $10.00 out · Google AI Studio $1.25 in / $10.00 out · and 2 more. Every provider

How to cite · data as of 2026-10-05

Gemini 2.5 Pro · benchmarks, pricing and providers. BenchGecko, data as of 2026-10-05. https://benchgecko.ai/model/gemini-2-5-pro

Credit "Source: BenchGecko" with a link. Prices per provider and Gecko Tests are BenchGecko data (CC BY 4.0); benchmark scores keep their original source, listed in the JSON. JSON · llms.txt · MCP