Claude Opus 4.6vsGPT-4o
Claude Opus 4.6 | GPT-4o | |
|---|---|---|
| Specifications | ||
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | — | 128k |
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $5.00 | $2.50 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $25.00 | $10.00 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.50 | $1.25 |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | $5.00Amazon Bedrock | $2.50Azure |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | $25.00Amazon Bedrock | $10.00Azure |
| Benchmarks | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 87% | 12% |
GPQA DiamondScience — Graduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | 91.3% | 49.9% |
| BenchmarksPublished by one model only | ||
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 80.8% | — |
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | 69% | — |
BrowseCompWeb browsing — Can the AI browse the web and track down hard-to-find answers? Higher is better. | 83.7% | — |
Humanity's Last Exam · with toolsMultidisciplinary reasoning — Humanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | 53% | — |
| Overview | ||
| Company | Anthropic | OpenAI |
| Release date | Feb 5 2026 | May 13 2024 |
| Access | Proprietary | Proprietary |
Other comparisons
Frequently asked questions
Claude Opus 4.6 leads GPT-4o on 2 of the 2 benchmarks they both report (BullshitBench v2, GPQA Diamond). GPT-4o is cheaper on both input and output: $2.50 vs $5.00 per million input tokens, and $10.00 vs $25.00 per million output tokens. GPT-4o shipped 633 days before Claude Opus 4.6, so benchmark comparisons should account for the intervening progress.
Published specifications for these two models are limited — see each model page for the latest details.
On BullshitBench v2, Claude Opus 4.6 leads at 87% vs GPT-4o at 12%. On GPQA Diamond, Claude Opus 4.6 leads at 91.3% vs GPT-4o at 49.9%.
Claude Opus 4.6 was released by Anthropic on Feb 5 2026.
GPT-4o was released by OpenAI on May 13 2024.
Claude Opus 4.6 leads on GPQA Diamond — Claude Opus 4.6 91.3% vs GPT-4o 49.9%.
GPT-4o is cheaper on both input and output: $2.50 vs $5.00 per million input tokens, and $10.00 vs $25.00 per million output tokens. Rates are pay-as-you-go API prices verified on August 18, 2026.