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Compare GPT-5.5, Claude Opus 4.7, and Gemini 3.1 Pro across public benchmark tables, with caveats on routing, availability, and methodology.
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Head-to-head comparison of GPT-5.4, Claude Opus/Sonnet 4.6, and Gemini 3.1 Pro — benchmarks, pricing, and deployment strategy for March 2026.
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Google's Gemini 3.1 Pro achieves 94.3% on GPQA Diamond and 77.1% on ARC-AGI-2 at $2/12 per million tokens — but NotebookLM regressions expose benchmark optimization trade-offs.
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Claude Opus 4.6 is the first commercial model classified at ASL-3 — Anthropic's designation for systems capable of autonomous action with real-world consequences. GPT-5.3-Codex earns the first "High" cybersecurity classification under OpenAI's Preparedness Framework, scoring 77.6% on CyberSec CTF. Documented incidents of token theft,
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Claude Opus 4.6 at $5/$25 per million tokens competes directly with GPT-5.2 at $1.75/$14. Gemini 3.1 Pro's $1.25/$10 leads on raw rates, but aggressive caching and first-pass accuracy shift the calculus. The economics of intelligence are more nuanced than headline token prices suggest. Beyond
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On SWE-bench Verified, Claude and Gemini are in a dead heat at 80.6-80.8%. Then GPT-5.3-Codex enters the arena, dominating Terminal-Bench 2.0 at 77.3% from isolated cloud sandboxes. The real differentiation is three-way: Claude's dynamic Agent Teams vs Gemini's sub-agent delegation vs Codex's async cloud
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The most consequential capability gap between frontier models is not performance on benchmarks — it is modality coverage and execution paradigm. Gemini processes five input types natively. Claude processes two with superior depth. GPT-5.3-Codex adds a third dimension: autonomous computer use, scoring 64.7% on
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Three frontier models, three architectural philosophies. Claude leads in output capacity (128K tokens) and raw throughput (107 t/s). Gemini processes 1M tokens across five native modalities at 66 t/s. GPT-5.3-Codex brings a coding-optimized 400K context with 93 t/s throughput in isolated cloud sandboxes. All
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February 2026 marks the definitive industrial transition from prompt-response chatbots to autonomous agent architectures. Claude Opus 4.6, Gemini 3.1 Pro, and OpenAI's GPT-5.3-Codex embody three fundamentally divergent strategies for the agentic era — depth and safety, breadth and multimodal integration, and unified coding-agent dominance.
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