Claude Opus 4.6 vs GPT-5

Choose Claude Opus 4.6 if you want…

• ✓Higher intelligence (Artificial Analysis index 46)
• ✓Larger context window (1M)

Choose GPT-5 if you want…

• ✓Faster output (~100.1 tokens/sec)
• ✓Lower price ($3.44 / 1M blended)

Claude Opus 4.6

Opus 4.6 is the model researchers and engineers reach for when the problem genuinely cannot be chunked — loading an entire codebase, a year's worth of literature, or a complex multi-part investigation into a single session of up to 750,000 words. It tops Terminal-Bench 2.0 among frontier models for agentic coding tasks and leads BrowseComp for hard-to-locate information retrieval, reflecting a design philosophy built around sustained, autonomous work rather than quick exchanges. Scientists have noted roughly double the accuracy on computational biology and structural chemistry tasks versus its predecessor. The tradeoff is speed: at 38.8 tokens per second, it feels noticeably slower than alternatives during interactive back-and-forth. The 1M-token window is also still in beta, and users report meaningful performance degradation well before hitting its ceiling. Best suited to high-stakes tasks where depth matters more than pace.

GPT-5

GPT-5 is OpenAI's unified flagship — a single model that scales its reasoning effort up or down to match the task, rather than making you pick a separate variant. The result shows up most clearly in hard technical work: a perfect AIME 2025 score with tools, 74.9% on SWE-bench Verified, and a 1.6% error rate on medical benchmark HealthBench make it one of the more capable models available for code, math, and domain-specific research. Its 400,000-token context window handles large codebases and lengthy documents without truncation. Users consistently praise the step-up in accuracy and the meaningful reduction in hallucinations over GPT-4o. The honest caveat: GPT-5 trades warmth for precision. Early adopters widely noted that responses are shorter, cooler, and noticeably less conversational than its predecessor — a real shift if personality and back-and-forth rapport matter to your workflow. Latency is also substantial; extended reasoning produces a time-to-first-token around 68 seconds, which rules it out for anything requiring snappy replies.