Compare · ModelsLive · 2 picked · head to head
Claude Opus 4 vs GPT-5.1
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
GPT-5.1 wins on 10/13 benchmarks
GPT-5.1 wins 10 of 13 shared benchmarks. Leads in reasoning · math · knowledge.
Category leads
reasoning·GPT-5.1math·GPT-5.1knowledge·GPT-5.1coding·GPT-5.1
Hype vs Reality
Attention vs performance
Claude Opus 4
#133 by perf·no signal
GPT-5.1
#97 by perf·no signal
Best value
GPT-5.1
9.5x better value than Claude Opus 4
Claude Opus 4
0.9 pts/$
$45.00/M
GPT-5.1
8.8 pts/$
$5.63/M
Vendor risk
Who is behind the model
Anthropic
$380.0B·Tier 1
OpenAI
$840.0B·Tier 1
Head to head
13 benchmarks · 2 models
Claude Opus 4GPT-5.1
ARC-AGI
GPT-5.1 leads by +37.1
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
Claude Opus 4
35.7
GPT-5.1
72.8
ARC-AGI-2
GPT-5.1 leads by +9.0
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
8.6
GPT-5.1
17.6
FrontierMath-2025-02-28-Private
GPT-5.1 leads by +26.6
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
Claude Opus 4
4.5
GPT-5.1
31.0
FrontierMath-Tier-4-2025-07-01-Private
GPT-5.1 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 Opus 4
4.2
GPT-5.1
12.5
GPQA diamond
GPT-5.1 leads by +15.2
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
68.3
GPT-5.1
83.5
GSO-Bench
GPT-5.1 leads by +6.8
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
6.9
GPT-5.1
13.7
HLE
GPT-5.1 leads by +13.6
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
6.2
GPT-5.1
19.8
OTIS Mock AIME 2024-2025
GPT-5.1 leads by +24.2
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Claude Opus 4
64.4
GPT-5.1
88.6
SimpleBench
Claude Opus 4 leads by +6.7
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
Claude Opus 4
50.6
GPT-5.1
43.8
SWE-Bench verified
Claude Opus 4 leads by +2.7
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
70.7
GPT-5.1
68.0
SWE-Bench Verified (Bash Only)
Claude Opus 4 leads by +1.6
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 Opus 4
67.6
GPT-5.1
66.0
VPCT
GPT-5.1 leads by +31.0
VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations.
Claude Opus 4
7.0
GPT-5.1
38.0
WeirdML
GPT-5.1 leads by +17.4
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
Claude Opus 4
43.4
GPT-5.1
60.8
Full benchmark table
| Benchmark | Claude Opus 4 | GPT-5.1 |
|---|---|---|
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | 35.7 | 72.8 |
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. | 8.6 | 17.6 |
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. | 4.5 | 31.0 |
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 | 12.5 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 68.3 | 83.5 |
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. | 6.9 | 13.7 |
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%. | 6.2 | 19.8 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | 64.4 | 88.6 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 50.6 | 43.8 |
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. | 70.7 | 68.0 |
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. | 67.6 | 66.0 |
VPCT VPCT (Visual Pattern Completion Test) · tests visual reasoning and pattern recognition by having models complete visual sequences and transformations. | 7.0 | 38.0 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 43.4 | 60.8 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $15.00 | $75.00 | 200K tokens (~100 books) | $300.00 | |
| $1.25 | $10.00 | 400K tokens (~200 books) | $34.38 |
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