Compare · ModelsLive · 3 picked · head to head
GPT-5.3-Codex vs Claude Opus 4.6 vs GPT-5.2
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Opus 4.6 wins on 12/18 benchmarks
Claude Opus 4.6 wins 12 of 18 shared benchmarks. Leads in knowledge · coding · reasoning.
Category leads
agentic·GPT-5.2knowledge·Claude Opus 4.6coding·Claude Opus 4.6reasoning·Claude Opus 4.6arena·Claude Opus 4.6math·Claude Opus 4.6
Hype vs Reality
Attention vs performance
GPT-5.3-Codex
#86 by perf·no signal
Claude Opus 4.6
#56 by perf·#4 by attention
GPT-5.2
#76 by perf·no signal
Best value
GPT-5.2
1.0x better value than GPT-5.3-Codex
GPT-5.3-Codex
6.6 pts/$
$7.88/M
Claude Opus 4.6
3.8 pts/$
$15.00/M
GPT-5.2
6.9 pts/$
$7.88/M
Vendor risk
Who is behind the model
OpenAI
$840.0B·Tier 1
Anthropic
$380.0B·Tier 1
OpenAI
$840.0B·Tier 1
Head to head
18 benchmarks · 3 models
GPT-5.3-CodexClaude Opus 4.6GPT-5.2
APEX-Agents
GPT-5.2 leads by +2.6
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
GPT-5.3-Codex
31.7
Claude Opus 4.6
31.7
GPT-5.2
34.3
PostTrainBench
Claude Opus 4.6 leads by +1.8
GPT-5.3-Codex
17.8
Claude Opus 4.6
23.2
GPT-5.2
21.4
SWE-Bench verified
Claude Opus 4.6 leads by +3.9
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.
GPT-5.3-Codex
74.8
Claude Opus 4.6
78.7
GPT-5.2
73.8
Terminal Bench
GPT-5.3-Codex leads by +2.6
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.
GPT-5.3-Codex
77.3
Claude Opus 4.6
74.7
GPT-5.2
64.9
WeirdML
GPT-5.3-Codex leads by +1.4
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
GPT-5.3-Codex
79.3
Claude Opus 4.6
77.9
GPT-5.2
72.2
ARC-AGI
Claude Opus 4.6 leads by +7.8
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
Claude Opus 4.6
94.0
GPT-5.2
86.2
ARC-AGI-2
Claude Opus 4.6 leads by +16.3
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 4.6
69.2
GPT-5.2
52.9
Chatbot Arena Elo · Coding
Claude Opus 4.6 leads by +139.8
Claude Opus 4.6
1542.9
GPT-5.2
1403.1
Chatbot Arena Elo · Overall
Claude Opus 4.6 leads by +57.1
Claude Opus 4.6
1496.6
GPT-5.2
1439.5
Chess Puzzles
GPT-5.2 leads by +32.0
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
Claude Opus 4.6
17.0
GPT-5.2
49.0
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.
Claude Opus 4.6
40.7
GPT-5.2
40.7
FrontierMath-Tier-4-2025-07-01-Private
Claude Opus 4.6 leads by +4.1
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 4.6
22.9
GPT-5.2
18.8
GPQA diamond
GPT-5.2 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 Opus 4.6
87.4
GPT-5.2
88.5
GSO-Bench
Claude Opus 4.6 leads by +5.9
GSO-Bench · evaluates AI models on real-world open-source software engineering tasks, testing the ability to understand and resolve actual GitHub issues.
Claude Opus 4.6
33.3
GPT-5.2
27.4
HLE
Claude Opus 4.6 leads by +7.0
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 4.6
31.1
GPT-5.2
24.2
OTIS Mock AIME 2024-2025
GPT-5.2 leads by +1.7
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Claude Opus 4.6
94.4
GPT-5.2
96.1
SimpleBench
Claude Opus 4.6 leads by +26.2
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Claude Opus 4.6
61.1
GPT-5.2
35.0
SimpleQA Verified
Claude Opus 4.6 leads by +7.6
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
Claude Opus 4.6
46.5
GPT-5.2
38.9
Full benchmark table
| Benchmark | GPT-5.3-Codex | Claude Opus 4.6 | GPT-5.2 |
|---|---|---|---|
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | 31.7 | 31.7 | 34.3 |
PostTrainBench | 17.8 | 23.2 | 21.4 |
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. | 74.8 | 78.7 | 73.8 |
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. | 77.3 | 74.7 | 64.9 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 79.3 | 77.9 | 72.2 |
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | — | 94.0 | 86.2 |
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. | — | 69.2 | 52.9 |
Chatbot Arena Elo · Coding | — | 1542.9 | 1403.1 |
Chatbot Arena Elo · Overall | — | 1496.6 | 1439.5 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | — | 17.0 | 49.0 |
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. | — | 40.7 | 40.7 |
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. | — | 22.9 | 18.8 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | — | 87.4 | 88.5 |
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. | — | 33.3 | 27.4 |
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%. | — | 31.1 | 24.2 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | — | 94.4 | 96.1 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | — | 61.1 | 35.0 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | — | 46.5 | 38.9 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $1.75 | $14.00 | 400K tokens (~200 books) | $48.13 | |
| $5.00 | $25.00 | 1.0M tokens (~500 books) | $100.00 | |
| $1.75 | $14.00 | 400K tokens (~200 books) | $48.13 |