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Claude Opus 5 Is Here: Fable 5 Intelligence at Half the Price

RAXXO Studios 2026年07月26日 08:01 8 次阅读 来源:Dev.to

Anthropic shipped Claude Opus 5 on July 24, calling it a step-change over Opus 4.8, not a routine bump The model runs a 1M token context window as both default and maximum, 128k max output tokens, with thinking on by default Anthropic says it approaches Fable 5 intelligence at roughly half the price, with per-token pricing unchanged from Opus 4.8 It shipped everywhere at once, the Claude API, AWS, Google Cloud, and Microsoft Foundry, and is now the default Opus model in Claude Code What Anthropic Actually Shipped On July 24, Anthropic released Claude Opus 5, and the framing in its own documentation is unusually direct about what kind of release this is. Anthropic calls it a step-change improvement over Claude Opus 4.8, not an incremental one, and says the largest gains land in deep reasoning, agentic coding and long-horizon tasks, and test-time compute scaling. That is a specific claim, not marketing language, and it matches how the model is positioned everywhere else in the announcement: as a model built to stay on task across long tool-use loops rather than one built to win a single benchmark screenshot. The capability list is long and mostly practical. Anthropic highlights better code review and bug-finding, with a high hit rate on real bugs and few false positives, holding up even at lower effort levels. It highlights vision improvements, reading charts, documents, and diagrams, and replicating UI and frontend visuals when the model has tools to crop and check its own work. It highlights office and document tasks, generating multi-sheet spreadsheets with real formulas and structured slide decks, and multi-agent coordination, running teams of subagents with writer-verifier patterns and fewer cases of agents stepping on each other's output. What stands out is that this is not a model pitched as a smarter chat assistant. Every capability on the list points at the same audience: people running Claude inside an agent loop, a coding session, or a multi-step workflow,

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