Compare · ModelsLive · 3 picked · head to head

Claude Sonnet 4.5 vs Gemini 2.5 Pro vs GPT-5

Side by side · benchmarks, pricing, and signals you can act on.

Winner summary

GPT-5 wins 26 of 39 shared benchmarks. Leads in knowledge · general · math.

Category leads
reasoning·Gemini 2.5 Proknowledge·GPT-5general·GPT-5math·GPT-5coding·GPT-5agentic·GPT-5language·GPT-5
Hype vs Reality
Claude Sonnet 4.5
#207 by perf·#10 by attention
OVERHYPED
Gemini 2.5 Pro
#116 by perf·no signal
QUIET
GPT-5
#100 by perf·#4 by attention
DESERVED
Best value
1.0x better value than Gemini 2.5 Pro
Claude Sonnet 4.5
4.2 pts/$
$9.00/M
Gemini 2.5 Pro
9.0 pts/$
$5.63/M
GPT-5
9.4 pts/$
$5.63/M
Vendor risk
Anthropic logo
Anthropic
$965.0B·Tier 1
Medium risk
Google DeepMind logo
Google DeepMind
$4.20T·Tier 1
Low risk
OpenAI logo
OpenAI
$840.0B·Tier 1
Medium risk
Head to head
Claude Sonnet 4.5Gemini 2.5 ProGPT-5
ARC-AGI
GPT-5 leads by +2.0
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
Claude Sonnet 4.5
63.7
Gemini 2.5 Pro
41.0
GPT-5
65.7
ARC-AGI-2
Claude Sonnet 4.5 leads by +3.8
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
Claude Sonnet 4.5
13.6
Gemini 2.5 Pro
4.9
GPT-5
9.9
Chess Puzzles
GPT-5 leads by +17.9
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Claude Sonnet 4.5
7.4
Gemini 2.5 Pro
15.8
GPT-5
33.7
DeepResearch Bench
Claude Sonnet 4.5 leads by +3.0
DeepResearch Bench · evaluates AI on complex multi-step research tasks requiring information gathering, synthesis, and producing comprehensive analyses.
Claude Sonnet 4.5
52.6
Gemini 2.5 Pro
42.8
GPT-5
49.6
Dtbench
GPT-5 leads by +12.5
Claude Sonnet 4.5
72.0
Gemini 2.5 Pro
70.7
GPT-5
84.5
FrontierMath-2025-02-28-Private
GPT-5 leads by +17.2
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
Claude Sonnet 4.5
15.2
Gemini 2.5 Pro
14.1
GPT-5
32.4
FrontierMath-Tier-4-2025-07-01-Private
GPT-5 leads by +8.3
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
Claude Sonnet 4.5
4.2
Gemini 2.5 Pro
4.2
GPT-5
12.5
FrontierMath-Tier-4-v2-Private
GPT-5 leads by +19.5
Claude Sonnet 4.5
2.4
Gemini 2.5 Pro
0.0
GPT-5
21.9
FrontierMath-Tiers-1-3-v2-Private
GPT-5 leads by +30.9
Claude Sonnet 4.5
23.9
Gemini 2.5 Pro
24.6
GPT-5
55.4
Gdpval
Claude Sonnet 4.5 leads by +7.7
Claude Sonnet 4.5
42.5
Gemini 2.5 Pro
23.3
GPT-5
34.8
GPQA diamond
GPT-5 leads by +1.2
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
Claude Sonnet 4.5
76.4
Gemini 2.5 Pro
80.4
GPT-5
81.6
GSO-Bench
Claude Sonnet 4.5 leads by +7.9
GSO-Bench · evaluates AI models on real-world open-source software engineering tasks, testing the ability to understand and resolve actual GitHub issues.
Claude Sonnet 4.5
14.7
Gemini 2.5 Pro
3.9
GPT-5
6.9
HLE
GPT-5 leads by +3.9
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 Sonnet 4.5
9.4
Gemini 2.5 Pro
17.7
GPT-5
21.6
Lmca
GPT-5 leads by +1.4
Claude Sonnet 4.5
45.6
Gemini 2.5 Pro
40.9
GPT-5
47.0
MATH level 5
GPT-5 leads by +0.4
MATH Level 5 · the hardest tier of the MATH benchmark, featuring competition-level problems from AMC, AIME, and Olympiad-style mathematics.
Claude Sonnet 4.5
97.7
Gemini 2.5 Pro
95.6
GPT-5
98.1
Metr Time Horizons
GPT-5 leads by +2.2
Claude Sonnet 4.5
67.4
Gemini 2.5 Pro
55.4
GPT-5
69.6
OTIS Mock AIME 2024-2025
GPT-5 leads by +6.7
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Claude Sonnet 4.5
77.8
Gemini 2.5 Pro
84.7
GPT-5
91.4
Remote Labor Index
Claude Sonnet 4.5 leads by +0.4
Claude Sonnet 4.5
2.1
Gemini 2.5 Pro
0.8
GPT-5
1.7
SimpleBench
Gemini 2.5 Pro leads by +6.8
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Claude Sonnet 4.5
45.2
Gemini 2.5 Pro
54.9
GPT-5
48.0
SimpleQA Verified
Gemini 2.5 Pro leads by +5.9
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Claude Sonnet 4.5
30.7
Gemini 2.5 Pro
56.0
GPT-5
50.1
SWE-Bench verified
GPT-5 leads by +2.3
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 Sonnet 4.5
71.3
Gemini 2.5 Pro
57.6
GPT-5
73.5
Terminal Bench
GPT-5 leads by +3.1
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 Sonnet 4.5
46.5
Gemini 2.5 Pro
32.6
GPT-5
49.6
VPCT
GPT-5 leads by +29.4
VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations.
Claude Sonnet 4.5
9.7
Gemini 2.5 Pro
19.6
GPT-5
49.0
WeirdML
GPT-5 leads by +6.7
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Claude Sonnet 4.5
47.7
Gemini 2.5 Pro
54.0
GPT-5
60.7
Aider polyglot
GPT-5 leads by +4.9
Aider Polyglot · measures how well AI models can edit code across multiple programming languages using the Aider coding assistant framework.
Gemini 2.5 Pro
83.1
GPT-5
88.0
APEX-Agents
GPT-5 leads by +11.7
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Gemini 2.5 Pro
6.6
GPT-5
18.3
Balrog
Gemini 2.5 Pro leads by +10.5
Balrog · benchmarks AI agents on text-based adventure games, testing language understanding, strategic planning, and long-horizon reasoning.
Gemini 2.5 Pro
43.3
GPT-5
32.8
Ebr Bench
GPT-5 leads by +10.3
Claude Sonnet 4.5
2.4
GPT-5
12.7
Fiction.LiveBench
GPT-5 leads by +5.5
Fiction.LiveBench · a continuously updated benchmark using recently published fiction to test reading comprehension and reasoning, preventing data contamination.
Gemini 2.5 Pro
91.7
GPT-5
97.2
GeoBench
GeoBench · tests geographic knowledge and spatial reasoning across countries, landmarks, coordinates, and geopolitical understanding.
Gemini 2.5 Pro
81.0
GPT-5
81.0
HELM · GPQA
GPT-5 leads by +4.2
Gemini 2.5 Pro
74.9
GPT-5
79.1
HELM · IFEval
GPT-5 leads by +3.5
Gemini 2.5 Pro
84.0
GPT-5
87.5
HELM · MMLU-Pro
Gemini 2.5 Pro
86.3
GPT-5
86.3
HELM · Omni-MATH
GPT-5 leads by +23.1
Gemini 2.5 Pro
41.6
GPT-5
64.7
HELM · WildBench
Gemini 2.5 Pro
85.7
GPT-5
85.7
Lech Mazur Writing
GPT-5 leads by +2.2
Lech Mazur Writing · evaluates creative writing ability, assessing prose quality, narrative coherence, and stylistic sophistication.
Gemini 2.5 Pro
83.8
GPT-5
86.0
Mystery Game Puzzles
GPT-5 leads by +6.6
Claude Sonnet 4.5
8.6
GPT-5
15.2
Proofbench
Claude Sonnet 4.5 leads by +1.0
Claude Sonnet 4.5
19.0
GPT-5
18.0
SWE-Bench Verified (Bash Only)
Claude Sonnet 4.5 leads by +5.6
SWE-Bench Verified (Bash Only) · a curated subset of SWE-bench where models fix real Python repository bugs using only bash commands, no agent frameworks.
Claude Sonnet 4.5
70.6
GPT-5
65.0
Full benchmark table
BenchmarkClaude Sonnet 4.5Gemini 2.5 ProGPT-5
ARC-AGI
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
63.741.065.7
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.
13.64.99.9
Chess Puzzles
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
7.415.833.7
DeepResearch Bench
DeepResearch Bench · evaluates AI on complex multi-step research tasks requiring information gathering, synthesis, and producing comprehensive analyses.
52.642.849.6
Dtbench
72.070.784.5
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.
15.214.132.4
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.
4.24.212.5
FrontierMath-Tier-4-v2-Private
2.40.021.9
FrontierMath-Tiers-1-3-v2-Private
23.924.655.4
Gdpval
42.523.334.8
GPQA diamond
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
76.480.481.6
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.
14.73.96.9
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%.
9.417.721.6
Lmca
45.640.947.0
MATH level 5
MATH Level 5 · the hardest tier of the MATH benchmark, featuring competition-level problems from AMC, AIME, and Olympiad-style mathematics.
97.795.698.1
Metr Time Horizons
67.455.469.6
OTIS Mock AIME 2024-2025
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
77.884.791.4
Remote Labor Index
2.10.81.7
SimpleBench
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
45.254.948.0
SimpleQA Verified
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
30.756.050.1
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.
71.357.673.5
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.
46.532.649.6
VPCT
VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations.
9.719.649.0
WeirdML
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
47.754.060.7
Aider polyglot
Aider Polyglot · measures how well AI models can edit code across multiple programming languages using the Aider coding assistant framework.
—83.188.0
APEX-Agents
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
—6.618.3
Balrog
Balrog · benchmarks AI agents on text-based adventure games, testing language understanding, strategic planning, and long-horizon reasoning.
—43.332.8
Ebr Bench
2.4—12.7
Fiction.LiveBench
Fiction.LiveBench · a continuously updated benchmark using recently published fiction to test reading comprehension and reasoning, preventing data contamination.
—91.797.2
GeoBench
GeoBench · tests geographic knowledge and spatial reasoning across countries, landmarks, coordinates, and geopolitical understanding.
—81.081.0
HELM · GPQA
—74.979.1
HELM · IFEval
—84.087.5
HELM · MMLU-Pro
—86.386.3
HELM · Omni-MATH
—41.664.7
HELM · WildBench
—85.785.7
Lech Mazur Writing
Lech Mazur Writing · evaluates creative writing ability, assessing prose quality, narrative coherence, and stylistic sophistication.
—83.886.0
Mystery Game Puzzles
8.6—15.2
Proofbench
19.0—18.0
SWE-Bench Verified (Bash Only)
SWE-Bench Verified (Bash Only) · a curated subset of SWE-bench where models fix real Python repository bugs using only bash commands, no agent frameworks.
70.6—65.0
Pricing · per 1M tokens · projected $/mo at 10M tokens
ModelInputOutputContextProjected $/mo
Anthropic logoClaude Sonnet 4.5$3.00$15.001.0M tokens (~500 books)$60.00
Google DeepMind logoGemini 2.5 Pro$1.25$10.001.0M tokens (~524 books)$34.38
OpenAI logoGPT-5$1.25$10.00400K tokens (~200 books)$34.38