Compare · ModelsLive · 3 picked · head to head

Gemini 3 Pro vs GPT-5 vs GPT-5 Chat

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

Winner summary

Gemini 3 Pro wins 24 of 30 shared benchmarks. Leads in knowledge · language · math.

Category leads
knowledge·Gemini 3 Prolanguage·Gemini 3 Promath·Gemini 3 Proreasoning·Gemini 3 Procoding·Gemini 3 Proagentic·Gemini 3 Proarena·Gemini 3 Progeneral·Gemini 3 Pro
Hype vs Reality
Gemini 3 Pro
#71 by perf·#5 by attention
DESERVED
GPT-5
#100 by perf·#4 by attention
DESERVED
GPT-5 Chat
#4 by perf·#4 by attention
DESERVED
Best value
1.5x better value than GPT-5
Gemini 3 Pro
n/a
no price
GPT-5
9.4 pts/$
$5.63/M
GPT-5 Chat
14.6 pts/$
$5.63/M
Vendor risk
Google DeepMind logo
Google DeepMind
$4.20T·Tier 1
Low risk
OpenAI logo
OpenAI
$840.0B·Tier 1
Medium risk
OpenAI logo
OpenAI
$840.0B·Tier 1
Medium risk
Head to head
Gemini 3 ProGPT-5GPT-5 Chat
HELM · GPQA
Gemini 3 Pro leads by +1.2
Gemini 3 Pro
80.3
GPT-5
79.1
GPT-5 Chat
79.1
HELM · IFEval
Gemini 3 Pro leads by +0.1
Gemini 3 Pro
87.6
GPT-5
87.5
GPT-5 Chat
87.5
HELM · MMLU-Pro
Gemini 3 Pro leads by +4.0
Gemini 3 Pro
90.3
GPT-5
86.3
GPT-5 Chat
86.3
HELM · Omni-MATH
Gemini 3 Pro
55.6
GPT-5
64.7
GPT-5 Chat
64.7
HELM · WildBench
Gemini 3 Pro leads by +0.2
Gemini 3 Pro
85.9
GPT-5
85.7
GPT-5 Chat
85.7
Aider polyglot
Aider Polyglot · measures how well AI models can edit code across multiple programming languages using the Aider coding assistant framework.
GPT-5
88.0
GPT-5 Chat
88.0
APEX-Agents
Gemini 3 Pro leads by +0.1
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Gemini 3 Pro
18.4
GPT-5
18.3
ARC-AGI
Gemini 3 Pro leads by +9.3
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
Gemini 3 Pro
75.0
GPT-5
65.7
ARC-AGI-2
Gemini 3 Pro leads by +21.3
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
Gemini 3 Pro
31.1
GPT-5
9.9
Chatbot Arena Elo · Overall
Gemini 3 Pro leads by +58.9
Gemini 3 Pro
1485.5
GPT-5 Chat
1426.6
Balrog
Gemini 3 Pro leads by +25.3
Balrog · benchmarks AI agents on text-based adventure games, testing language understanding, strategic planning, and long-horizon reasoning.
Gemini 3 Pro
58.1
GPT-5
32.8
Chess Puzzles
GPT-5 leads by +6.3
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Gemini 3 Pro
27.4
GPT-5
33.7
DeepResearch Bench
GPT-5 leads by +3.3
DeepResearch Bench · evaluates AI on complex multi-step research tasks requiring information gathering, synthesis, and producing comprehensive analyses.
Gemini 3 Pro
46.3
GPT-5
49.6
FrontierMath-2025-02-28-Private
Gemini 3 Pro leads by +33.5
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
Gemini 3 Pro
66.0
GPT-5
32.4
FrontierMath-Tier-4-2025-07-01-Private
Gemini 3 Pro leads by +18.8
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
Gemini 3 Pro
31.3
GPT-5
12.5
Gdpval
Gemini 3 Pro leads by +5.5
Gemini 3 Pro
40.3
GPT-5
34.8
GeoBench
Gemini 3 Pro leads by +3.0
GeoBench · tests geographic knowledge and spatial reasoning across countries, landmarks, coordinates, and geopolitical understanding.
Gemini 3 Pro
84.0
GPT-5
81.0
GPQA diamond
Gemini 3 Pro leads by +8.6
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
Gemini 3 Pro
90.2
GPT-5
81.6
GSO-Bench
Gemini 3 Pro leads by +11.8
GSO-Bench · evaluates AI models on real-world open-source software engineering tasks, testing the ability to understand and resolve actual GitHub issues.
Gemini 3 Pro
18.6
GPT-5
6.9
HLE
Gemini 3 Pro leads by +12.8
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%.
Gemini 3 Pro
34.4
GPT-5
21.6
Metr Time Horizons
Gemini 3 Pro leads by +1.4
Gemini 3 Pro
71.0
GPT-5
69.6
OTIS Mock AIME 2024-2025
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Gemini 3 Pro
91.4
GPT-5
91.4
Proofbench
Gemini 3 Pro leads by +2.0
Gemini 3 Pro
20.0
GPT-5
18.0
Remote Labor Index
GPT-5 leads by +0.4
Gemini 3 Pro
1.3
GPT-5
1.7
SimpleBench
Gemini 3 Pro leads by +23.6
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Gemini 3 Pro
71.7
GPT-5
48.0
SimpleQA Verified
Gemini 3 Pro leads by +22.8
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Gemini 3 Pro
72.9
GPT-5
50.1
SWE-Bench verified
GPT-5 leads by +0.6
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.
Gemini 3 Pro
72.9
GPT-5
73.5
Terminal Bench
Gemini 3 Pro leads by +19.8
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.
Gemini 3 Pro
69.4
GPT-5
49.6
VPCT
Gemini 3 Pro leads by +37.5
VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations.
Gemini 3 Pro
86.5
GPT-5
49.0
WeirdML
Gemini 3 Pro leads by +9.2
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Gemini 3 Pro
69.9
GPT-5
60.7
Full benchmark table
BenchmarkGemini 3 ProGPT-5GPT-5 Chat
HELM · GPQA
80.379.179.1
HELM · IFEval
87.687.587.5
HELM · MMLU-Pro
90.386.386.3
HELM · Omni-MATH
55.664.764.7
HELM · WildBench
85.985.785.7
Aider polyglot
Aider Polyglot · measures how well AI models can edit code across multiple programming languages using the Aider coding assistant framework.
—88.088.0
APEX-Agents
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
18.418.3—
ARC-AGI
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
75.065.7—
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.
31.19.9—
Chatbot Arena Elo · Overall
1485.5—1426.6
Balrog
Balrog · benchmarks AI agents on text-based adventure games, testing language understanding, strategic planning, and long-horizon reasoning.
58.132.8—
Chess Puzzles
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
27.433.7—
DeepResearch Bench
DeepResearch Bench · evaluates AI on complex multi-step research tasks requiring information gathering, synthesis, and producing comprehensive analyses.
46.349.6—
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.
66.032.4—
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.
31.312.5—
Gdpval
40.334.8—
GeoBench
GeoBench · tests geographic knowledge and spatial reasoning across countries, landmarks, coordinates, and geopolitical understanding.
84.081.0—
GPQA diamond
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
90.281.6—
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.
18.66.9—
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%.
34.421.6—
Metr Time Horizons
71.069.6—
OTIS Mock AIME 2024-2025
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
91.491.4—
Proofbench
20.018.0—
Remote Labor Index
1.31.7—
SimpleBench
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
71.748.0—
SimpleQA Verified
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
72.950.1—
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.
72.973.5—
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.
69.449.6—
VPCT
VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations.
86.549.0—
WeirdML
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
69.960.7—
Pricing · per 1M tokens · projected $/mo at 10M tokens
ModelInputOutputContextProjected $/mo
Google DeepMind logoGemini 3 Pro————
OpenAI logoGPT-5$1.25$10.00400K tokens (~200 books)$34.38
OpenAI logoGPT-5 Chat$1.25$10.00128K tokens (~64 books)$34.38