Compare · ModelsLive · 2 picked · head to head

o3 vs Gemini 3 Pro

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

Winner summary

Gemini 3 Pro wins 20 of 22 shared benchmarks. Leads in speed · reasoning · math.

Category leads
speed·Gemini 3 Proreasoning·Gemini 3 Promath·Gemini 3 Proknowledge·Gemini 3 Procoding·Gemini 3 Prolanguage·Gemini 3 Pro
Hype vs Reality
o3
#69 by perf·no signal
QUIET
Gemini 3 Pro
#40 by perf·no signal
QUIET
Best value
o3
11.0 pts/$
$5.00/M
Gemini 3 Pro
no price
Vendor risk
OpenAI logo
OpenAI
$840.0B·Tier 1
Medium risk
Google DeepMind logo
Google DeepMind
$4.00T·Tier 1
Low risk
Head to head
o3Gemini 3 Pro
Artificial Analysis · Agentic Index
Gemini 3 Pro leads by +9.0
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
o3
36.1
Gemini 3 Pro
45.0
Artificial Analysis · Coding Index
Gemini 3 Pro leads by +1.0
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
o3
38.4
Gemini 3 Pro
39.4
Artificial Analysis · Quality Index
Gemini 3 Pro leads by +2.9
o3
38.4
Gemini 3 Pro
41.3
ARC-AGI
Gemini 3 Pro leads by +14.2
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
o3
60.8
Gemini 3 Pro
75.0
ARC-AGI-2
Gemini 3 Pro leads by +24.6
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
o3
6.5
Gemini 3 Pro
31.1
FrontierMath-2025-02-28-Private
Gemini 3 Pro leads by +18.9
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
o3
18.7
Gemini 3 Pro
37.6
FrontierMath-Tier-4-2025-07-01-Private
Gemini 3 Pro leads by +16.7
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
o3
2.1
Gemini 3 Pro
18.8
GeoBench
Gemini 3 Pro leads by +10.0
GeoBench · tests geographic knowledge and spatial reasoning across countries, landmarks, coordinates, and geopolitical understanding.
o3
74.0
Gemini 3 Pro
84.0
GPQA diamond
Gemini 3 Pro leads by +14.4
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
o3
75.8
Gemini 3 Pro
90.2
GSO-Bench
Gemini 3 Pro leads by +9.8
GSO-Bench · evaluates AI models on real-world open-source software engineering tasks, testing the ability to understand and resolve actual GitHub issues.
o3
8.8
Gemini 3 Pro
18.6
HELM · GPQA
Gemini 3 Pro leads by +5.0
o3
75.3
Gemini 3 Pro
80.3
HELM · IFEval
Gemini 3 Pro leads by +0.7
o3
86.9
Gemini 3 Pro
87.6
HELM · MMLU-Pro
Gemini 3 Pro leads by +4.4
o3
85.9
Gemini 3 Pro
90.3
HELM · Omni-MATH
o3 leads by +15.8
o3
71.4
Gemini 3 Pro
55.6
HELM · WildBench
o3 leads by +0.2
o3
86.1
Gemini 3 Pro
85.9
HLE
Gemini 3 Pro leads by +18.1
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%.
o3
16.3
Gemini 3 Pro
34.4
OTIS Mock AIME 2024-2025
Gemini 3 Pro leads by +7.5
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
o3
83.9
Gemini 3 Pro
91.4
SimpleBench
Gemini 3 Pro leads by +28.0
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
o3
43.7
Gemini 3 Pro
71.7
SimpleQA Verified
Gemini 3 Pro leads by +19.9
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
o3
53.0
Gemini 3 Pro
72.9
SWE-Bench verified
Gemini 3 Pro leads by +10.6
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.
o3
62.3
Gemini 3 Pro
72.9
VPCT
Gemini 3 Pro leads by +58.5
VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations.
o3
28.0
Gemini 3 Pro
86.5
WeirdML
Gemini 3 Pro leads by +17.5
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
o3
52.4
Gemini 3 Pro
69.9
Full benchmark table
Benchmarko3Gemini 3 Pro
Artificial Analysis · Agentic Index
Artificial Analysis Agentic Index · a composite score measuring how well a model performs in agentic workflows · multi-step tool use, planning, error recovery, and autonomous task completion. Aggregates results from multiple agentic benchmarks including SWE-bench, tool-use tests, and planning evaluations. The canonical single-number metric for "how good is this model as an agent?"
36.145.0
Artificial Analysis · Coding Index
Artificial Analysis Coding Index · a composite score that aggregates performance across multiple coding benchmarks into a single index. Tracks code generation quality, debugging ability, multi-language competence, and real-world software engineering tasks. Used by Artificial Analysis to rank model coding capability in a normalized, comparable format. Useful for developers choosing between models for coding-heavy workloads.
38.439.4
Artificial Analysis · Quality Index
38.441.3
ARC-AGI
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
60.875.0
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.
6.531.1
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.
18.737.6
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.
2.118.8
GeoBench
GeoBench · tests geographic knowledge and spatial reasoning across countries, landmarks, coordinates, and geopolitical understanding.
74.084.0
GPQA diamond
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
75.890.2
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.
8.818.6
HELM · GPQA
75.380.3
HELM · IFEval
86.987.6
HELM · MMLU-Pro
85.990.3
HELM · Omni-MATH
71.455.6
HELM · WildBench
86.185.9
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%.
16.334.4
OTIS Mock AIME 2024-2025
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
83.991.4
SimpleBench
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
43.771.7
SimpleQA Verified
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
53.072.9
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.
62.372.9
VPCT
VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations.
28.086.5
WeirdML
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
52.469.9
Pricing · per 1M tokens · projected $/mo at 10M tokens
ModelInputOutputContextProjected $/mo
OpenAI logoo3$2.00$8.00200K tokens (~100 books)$35.00
Google DeepMind logoGemini 3 Pro