Claude Fable 5.1 vs GPT-6 Cyber

Where it leads

• Lower input and output prices, $10 and $50 vs $20 and $100 per 1M tokens
• Cheaper cached input, $0.25 vs $2 per 1M tokens
• Batch pricing, $5 input and $25 output per 1M tokens

Best for

• Long-horizon agentic coding where a large prompt prefix is replayed across many turns
• Work where Claude Opus 5 at higher effort has already been evaluated and fell short

Watch out for

• Base input and output pricing is unchanged from Fable 5 at $10 / $50; the saving is entirely in cache reads, so a workload with little cache reuse sees no discount
• 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 are not directly comparable across generations
• Anthropic’s launch comparisons are self-reported and were not reproduced independently here

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