Compare · ModelsLive · 2 picked · head to head
Claude Opus 4.5 vs Gemini 2.5 Pro
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Opus 4.5 wins on 23/28 benchmarks
Claude Opus 4.5 wins 23 of 28 shared benchmarks. Leads in agentic · reasoning · arena.
Category leads
agentic·Claude Opus 4.5reasoning·Claude Opus 4.5arena·Claude Opus 4.5knowledge·Claude Opus 4.5general·Claude Opus 4.5math·Claude Opus 4.5coding·Claude Opus 4.5
Hype vs Reality
Attention vs performance
Claude Opus 4.5
#179 by perf·#9 by attention
Gemini 2.5 Pro
#116 by perf·no signal
Best value
Gemini 2.5 Pro
3.3x better value than Claude Opus 4.5
Claude Opus 4.5
2.8 pts/$
$15.00/M
Gemini 2.5 Pro
9.0 pts/$
$5.63/M
Vendor risk
Who is behind the model
Anthropic
$965.0B·Tier 1
Google DeepMind
$4.20T·Tier 1
Head to head
28 benchmarks · 2 models
Claude Opus 4.5Gemini 2.5 Pro
APEX-Agents
Claude Opus 4.5 leads by +11.8
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Claude Opus 4.5
18.4
Gemini 2.5 Pro
6.6
ARC-AGI
Claude Opus 4.5 leads by +39.0
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
Claude Opus 4.5
80.0
Gemini 2.5 Pro
41.0
ARC-AGI-2
Claude Opus 4.5 leads by +32.8
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
Claude Opus 4.5
37.6
Gemini 2.5 Pro
4.9
Chatbot Arena Elo · Coding
Claude Opus 4.5 leads by +241.5
Claude Opus 4.5
1468.5
Gemini 2.5 Pro
1227.0
Chatbot Arena Elo · Overall
Claude Opus 4.5 leads by +24.2
Claude Opus 4.5
1469.8
Gemini 2.5 Pro
1445.6
Balrog
Claude Opus 4.5 leads by +0.2
Balrog · benchmarks AI agents on text-based adventure games, testing language understanding, strategic planning, and long-horizon reasoning.
Claude Opus 4.5
43.5
Gemini 2.5 Pro
43.3
Chess Puzzles
Gemini 2.5 Pro leads by +8.4
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Claude Opus 4.5
7.4
Gemini 2.5 Pro
15.8
DeepResearch Bench
Claude Opus 4.5 leads by +12.0
DeepResearch Bench · evaluates AI on complex multi-step research tasks requiring information gathering, synthesis, and producing comprehensive analyses.
Claude Opus 4.5
54.8
Gemini 2.5 Pro
42.8
Dtbench
Claude Opus 4.5 leads by +12.5
Claude Opus 4.5
83.1
Gemini 2.5 Pro
70.7
FrontierMath-2025-02-28-Private
Claude Opus 4.5 leads by +6.6
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
Claude Opus 4.5
20.7
Gemini 2.5 Pro
14.1
FrontierMath-Tier-4-2025-07-01-Private
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
Claude Opus 4.5
4.2
Gemini 2.5 Pro
4.2
FrontierMath-Tier-4-v2-Private
Claude Opus 4.5 leads by +4.9
Claude Opus 4.5
4.9
Gemini 2.5 Pro
0.0
FrontierMath-Tiers-1-3-v2-Private
Claude Opus 4.5 leads by +9.8
Claude Opus 4.5
34.4
Gemini 2.5 Pro
24.6
Gdpval
Claude Opus 4.5 leads by +22.2
Claude Opus 4.5
45.5
Gemini 2.5 Pro
23.3
GeoBench
Gemini 2.5 Pro leads by +6.0
GeoBench · tests geographic knowledge and spatial reasoning across countries, landmarks, coordinates, and geopolitical understanding.
Claude Opus 4.5
75.0
Gemini 2.5 Pro
81.0
GPQA diamond
Claude Opus 4.5 leads by +1.0
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
Claude Opus 4.5
81.4
Gemini 2.5 Pro
80.4
GSO-Bench
Claude Opus 4.5 leads by +22.6
GSO-Bench · evaluates AI models on real-world open-source software engineering tasks, testing the ability to understand and resolve actual GitHub issues.
Claude Opus 4.5
26.5
Gemini 2.5 Pro
3.9
HLE
Claude Opus 4.5 leads by +3.7
HLE (Humanity's Last Exam) · a reasoning benchmark designed to be the hardest public evaluation of AI. Questions span mathematics, physics, philosophy, and logic · curated to be at or beyond the frontier of human expert capability. Tested with and without tool augmentation. Claude Opus 4.7 scores 46.9% without tools and 54.7% with tools · making it one of the few benchmarks where the top score is below 60%.
Claude Opus 4.5
21.4
Gemini 2.5 Pro
17.7
Lmca
Claude Opus 4.5 leads by +11.4
Claude Opus 4.5
52.3
Gemini 2.5 Pro
40.9
Metr Time Horizons
Claude Opus 4.5 leads by +19.5
Claude Opus 4.5
75.0
Gemini 2.5 Pro
55.4
OTIS Mock AIME 2024-2025
Claude Opus 4.5 leads by +1.4
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Claude Opus 4.5
86.1
Gemini 2.5 Pro
84.7
Remote Labor Index
Claude Opus 4.5 leads by +2.9
Claude Opus 4.5
3.8
Gemini 2.5 Pro
0.8
SimpleBench
Gemini 2.5 Pro leads by +0.5
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Claude Opus 4.5
54.4
Gemini 2.5 Pro
54.9
SimpleQA Verified
Gemini 2.5 Pro leads by +14.2
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Claude Opus 4.5
41.8
Gemini 2.5 Pro
56.0
SWE-Bench verified
Claude Opus 4.5 leads by +19.1
SWE-bench Verified · 500 human-validated tasks from 12 real Python repositories (Django, Flask, scikit-learn, sympy, and others). Each task requires the model to produce a git patch that resolves a real GitHub issue and passes the test suite. The verified subset eliminates ambiguous tasks from the original SWE-bench. Claude Mythos Preview leads at 93.9%, crossing 90% for the first time in 2026. Opus 4.6 scores 80.8%. The benchmark remains the most-cited evaluation for code-generation capability.
Claude Opus 4.5
76.7
Gemini 2.5 Pro
57.6
Terminal Bench
Claude Opus 4.5 leads by +30.5
Terminal-Bench 2.0 · evaluates AI agents on real terminal-based coding tasks · writing scripts, debugging, running tests, and managing projects entirely through command-line interaction. Tests both code quality and terminal fluency. Claude Opus 4.7 scores 69.4%, demonstrating significant agentic terminal competence.
Claude Opus 4.5
63.1
Gemini 2.5 Pro
32.6
VPCT
Gemini 2.5 Pro leads by +9.6
VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations.
Claude Opus 4.5
10.0
Gemini 2.5 Pro
19.6
WeirdML
Claude Opus 4.5 leads by +9.7
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Claude Opus 4.5
63.7
Gemini 2.5 Pro
54.0
Full benchmark table
| Benchmark | Claude Opus 4.5 | Gemini 2.5 Pro |
|---|---|---|
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 18.4 | 6.6 |
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | 80.0 | 41.0 |
ARC-AGI-2 ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data. | 37.6 | 4.9 |
Chatbot Arena Elo · Coding | 1468.5 | 1227.0 |
Chatbot Arena Elo · Overall | 1469.8 | 1445.6 |
Balrog Balrog · benchmarks AI agents on text-based adventure games, testing language understanding, strategic planning, and long-horizon reasoning. | 43.5 | 43.3 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 7.4 | 15.8 |
DeepResearch Bench DeepResearch Bench · evaluates AI on complex multi-step research tasks requiring information gathering, synthesis, and producing comprehensive analyses. | 54.8 | 42.8 |
Dtbench | 83.1 | 70.7 |
FrontierMath-2025-02-28-Private FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning. | 20.7 | 14.1 |
FrontierMath-Tier-4-2025-07-01-Private FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning. | 4.2 | 4.2 |
FrontierMath-Tier-4-v2-Private | 4.9 | 0.0 |
FrontierMath-Tiers-1-3-v2-Private | 34.4 | 24.6 |
Gdpval | 45.5 | 23.3 |
GeoBench GeoBench · tests geographic knowledge and spatial reasoning across countries, landmarks, coordinates, and geopolitical understanding. | 75.0 | 81.0 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 81.4 | 80.4 |
GSO-Bench GSO-Bench · evaluates AI models on real-world open-source software engineering tasks, testing the ability to understand and resolve actual GitHub issues. | 26.5 | 3.9 |
HLE HLE (Humanity's Last Exam) · a reasoning benchmark designed to be the hardest public evaluation of AI. Questions span mathematics, physics, philosophy, and logic · curated to be at or beyond the frontier of human expert capability. Tested with and without tool augmentation. Claude Opus 4.7 scores 46.9% without tools and 54.7% with tools · making it one of the few benchmarks where the top score is below 60%. | 21.4 | 17.7 |
Lmca | 52.3 | 40.9 |
Metr Time Horizons | 75.0 | 55.4 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 86.1 | 84.7 |
Remote Labor Index | 3.8 | 0.8 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 54.4 | 54.9 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 41.8 | 56.0 |
SWE-Bench verified SWE-bench Verified · 500 human-validated tasks from 12 real Python repositories (Django, Flask, scikit-learn, sympy, and others). Each task requires the model to produce a git patch that resolves a real GitHub issue and passes the test suite. The verified subset eliminates ambiguous tasks from the original SWE-bench. Claude Mythos Preview leads at 93.9%, crossing 90% for the first time in 2026. Opus 4.6 scores 80.8%. The benchmark remains the most-cited evaluation for code-generation capability. | 76.7 | 57.6 |
Terminal Bench Terminal-Bench 2.0 · evaluates AI agents on real terminal-based coding tasks · writing scripts, debugging, running tests, and managing projects entirely through command-line interaction. Tests both code quality and terminal fluency. Claude Opus 4.7 scores 69.4%, demonstrating significant agentic terminal competence. | 63.1 | 32.6 |
VPCT VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations. | 10.0 | 19.6 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 63.7 | 54.0 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $5.00 | $25.00 | 200K tokens (~100 books) | $100.00 | |
| $1.25 | $10.00 | 1.0M tokens (~524 books) | $34.38 |