Compare · ModelsLive · 3 picked · head to head
GPT-5.4 Pro vs Gemini 3.1 Pro Preview vs Claude Opus 4.7
Side by side · benchmarks, pricing, and signals you can act on.
Winner summary
Claude Opus 4.7 wins on 11/20 benchmarks
Claude Opus 4.7 wins 11 of 20 shared benchmarks. Leads in math · coding · agentic.
Category leads
reasoning·Gemini 3.1 Pro Previewknowledge·GPT-5.4 Promath·Claude Opus 4.7coding·Claude Opus 4.7agentic·Claude Opus 4.7arena·Claude Opus 4.7
Hype vs Reality
Attention vs performance
GPT-5.4 Pro
#41 by perf·no signal
Gemini 3.1 Pro Preview
#74 by perf·no signal
Claude Opus 4.7
#65 by perf·no signal
Best value
Gemini 3.1 Pro Preview
2.1x better value than Claude Opus 4.7
GPT-5.4 Pro
0.6 pts/$
$105.00/M
Gemini 3.1 Pro Preview
8.1 pts/$
$7.00/M
Claude Opus 4.7
3.9 pts/$
$15.00/M
Vendor risk
Who is behind the model
OpenAI
$840.0B·Tier 1
Google DeepMind
$4.00T·Tier 1
Anthropic
$380.0B·Tier 1
Head to head
20 benchmarks · 3 models
GPT-5.4 ProGemini 3.1 Pro PreviewClaude Opus 4.7
ARC-AGI
Gemini 3.1 Pro Preview leads by +3.5
ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization.
GPT-5.4 Pro
94.5
Gemini 3.1 Pro Preview
98.0
Claude Opus 4.7
93.5
ARC-AGI-2
GPT-5.4 Pro leads by +6.2
ARC-AGI-2 · the second iteration of the Abstraction and Reasoning Corpus, testing novel pattern recognition and abstract reasoning without prior training data.
GPT-5.4 Pro
83.3
Gemini 3.1 Pro Preview
77.1
Claude Opus 4.7
75.8
Chess Puzzles
GPT-5.4 Pro leads by +3.6
Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities.
GPT-5.4 Pro
58.6
Gemini 3.1 Pro Preview
55.0
Claude Opus 4.7
30.0
FrontierMath-2025-02-28-Private
GPT-5.4 Pro leads by +6.2
FrontierMath (Feb 2025) · original research-level math problems created by mathematicians, testing capabilities at the boundary of current AI mathematical reasoning.
GPT-5.4 Pro
50.0
Gemini 3.1 Pro Preview
36.9
Claude Opus 4.7
43.8
FrontierMath-Tier-4-2025-07-01-Private
GPT-5.4 Pro leads by +14.6
FrontierMath Tier 4 (Jul 2025) · the most challenging tier of frontier mathematics, containing problems that push the absolute limits of AI mathematical reasoning.
GPT-5.4 Pro
37.5
Gemini 3.1 Pro Preview
16.7
Claude Opus 4.7
22.9
GPQA diamond
GPT-5.4 Pro leads by +0.7
Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs.
GPT-5.4 Pro
92.8
Gemini 3.1 Pro Preview
92.1
Claude Opus 4.7
86.9
HLE
Gemini 3.1 Pro Preview leads by +2.2
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%.
GPT-5.4 Pro
41.5
Gemini 3.1 Pro Preview
43.7
Claude Opus 4.7
33.0
SimpleBench
Gemini 3.1 Pro Preview leads by +6.6
SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking.
GPT-5.4 Pro
68.9
Gemini 3.1 Pro Preview
75.5
Claude Opus 4.7
55.5
SimpleQA Verified
Gemini 3.1 Pro Preview leads by +26.7
SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information.
GPT-5.4 Pro
47.8
Gemini 3.1 Pro Preview
77.3
Claude Opus 4.7
50.6
WeirdML
Claude Opus 4.7 leads by +4.3
WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns.
GPT-5.4 Pro
57.4
Gemini 3.1 Pro Preview
72.1
Claude Opus 4.7
76.4
APEX-Agents
Claude Opus 4.7 leads by +0.4
APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments.
Gemini 3.1 Pro Preview
33.5
Claude Opus 4.7
33.9
Chatbot Arena Elo · Coding
Claude Opus 4.7 leads by +109.9
Gemini 3.1 Pro Preview
1447.0
Claude Opus 4.7
1556.9
Chatbot Arena Elo · Overall
Claude Opus 4.7 leads by +6.7
Gemini 3.1 Pro Preview
1486.4
Claude Opus 4.7
1493.1
FrontierMath-Tier-4-v2-Private
Claude Opus 4.7 leads by +4.9
Gemini 3.1 Pro Preview
26.8
Claude Opus 4.7
31.7
FrontierMath-Tiers-1-3-v2-Private
Claude Opus 4.7 leads by +10.5
Gemini 3.1 Pro Preview
59.6
Claude Opus 4.7
70.2
GSO-Bench
Claude Opus 4.7 leads by +21.6
GSO-Bench · evaluates AI models on real-world open-source software engineering tasks, testing the ability to understand and resolve actual GitHub issues.
Gemini 3.1 Pro Preview
22.6
Claude Opus 4.7
44.1
OTIS Mock AIME 2024-2025
Claude Opus 4.7 leads by +2.2
OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills.
Gemini 3.1 Pro Preview
95.6
Claude Opus 4.7
97.8
PostTrainBench
Claude Opus 4.7 leads by +7.0
Gemini 3.1 Pro Preview
21.6
Claude Opus 4.7
28.6
SWE-Bench verified
Claude Opus 4.7 leads by +7.8
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 3.1 Pro Preview
75.6
Claude Opus 4.7
83.5
Terminal Bench
Claude Opus 4.7 leads by +10.0
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 3.1 Pro Preview
80.2
Claude Opus 4.7
90.2
Full benchmark table
| Benchmark | GPT-5.4 Pro | Gemini 3.1 Pro Preview | Claude Opus 4.7 |
|---|---|---|---|
ARC-AGI ARC-AGI · the original Abstraction and Reasoning Corpus, testing whether AI can solve novel visual pattern recognition tasks without memorization. | 94.5 | 98.0 | 93.5 |
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. | 83.3 | 77.1 | 75.8 |
Chess Puzzles Chess Puzzles · tests strategic and tactical reasoning by having models solve chess puzzle positions, evaluating lookahead and pattern recognition abilities. | 58.6 | 55.0 | 30.0 |
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. | 50.0 | 36.9 | 43.8 |
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. | 37.5 | 16.7 | 22.9 |
GPQA diamond Graduate-Level Google-Proof QA (Diamond set) · expert-crafted questions in physics, biology, and chemistry that are difficult even for domain PhDs. | 92.8 | 92.1 | 86.9 |
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%. | 41.5 | 43.7 | 33.0 |
SimpleBench SimpleBench · tests fundamental reasoning capabilities with straightforward problems designed to expose gaps in basic logical and spatial thinking. | 68.9 | 75.5 | 55.5 |
SimpleQA Verified SimpleQA Verified · short factual questions with verified answers, measuring factual accuracy and the tendency to hallucinate or provide incorrect information. | 47.8 | 77.3 | 50.6 |
WeirdML WeirdML · tests models on unusual and adversarial machine learning tasks that require creative problem-solving beyond standard patterns. | 57.4 | 72.1 | 76.4 |
APEX-Agents APEX-Agents · evaluates AI agents on complex, multi-step tasks requiring planning, tool use, and autonomous decision-making in realistic environments. | — | 33.5 | 33.9 |
Chatbot Arena Elo · Coding | — | 1447.0 | 1556.9 |
Chatbot Arena Elo · Overall | — | 1486.4 | 1493.1 |
FrontierMath-Tier-4-v2-Private | — | 26.8 | 31.7 |
FrontierMath-Tiers-1-3-v2-Private | — | 59.6 | 70.2 |
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. | — | 22.6 | 44.1 |
OTIS Mock AIME 2024-2025 OTIS Mock AIME 2024-2025 · simulated American Invitational Mathematics Examination problems testing advanced problem-solving skills. | — | 95.6 | 97.8 |
PostTrainBench | — | 21.6 | 28.6 |
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. | — | 75.6 | 83.5 |
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. | — | 80.2 | 90.2 |
Pricing · per 1M tokens · projected $/mo at 10M tokens
| Model | Input | Output | Context | Projected $/mo |
|---|---|---|---|---|
| $30.00 | $180.00 | 1.1M tokens (~525 books) | $675.00 | |
| $2.00 | $12.00 | 1.0M tokens (~524 books) | $45.00 | |
| $5.00 | $25.00 | 1.0M tokens (~500 books) | $100.00 |