Claude Opus 5.5 vs GPT-6 Cyber

Where it leads

• Lower input and output prices, $4 and $20 vs $20 and $100 per 1M tokens
• Cheaper cached input, $0.20 vs $2 per 1M tokens
• Batch pricing, $2 input and $10 output per 1M tokens

Best for

• Long-running agentic coding and knowledge work as the general-purpose default
• Cache-heavy agent loops where the 0.05x read multiplier compounds

Watch out for

• The API effort default is medium here, not high as on Claude Fable 5.1 and Claude Sonnet 5.5, so a like-for-like comparison has to set effort explicitly
• The 4.7-generation tokenizer produces roughly 30% more tokens for the same text than Claude Sonnet 4.6 and earlier, so per-token rates do not compare directly across generations

Where it leads

• Larger context window 1,050,000 vs 1,000,000 tokens

Best for

• Security teams approved for Daybreak Red that develop and validate exploits in authorized tests
• Vulnerability research and patch validation across large codebases such as browsers and kernels

Watch out for

• Limited access: OpenAI is rolling it out through the API and Codex to select approved Daybreak Red customers first, with identity verification, single sign-on, multi-factor authentication and API IP allowlisting
• OpenAI rates it Critical in cybersecurity under its Preparedness Framework, like GPT-6 Astra and up from High for GPT-5.6 Cyber, and adds checks that block high-risk activity against critical systems
• It does not beat GPT-6 Astra at general coding (82.95% against 83.24% on OpenAI's internal ExpertSWE), and on Irregular's FrontierCyber it solved 90 of 288 challenges against 96 for Astra; no independent benchmark score is recorded here yet