Simon Willison's Weblog·2 months ago·
53
● 17 sources
Anthropic released Claude Opus 5, a new large language model that leads the Artificial Analysis leaderboard and matches Claude Opus 4.8 in price. The model demonstrated the ability to independently write a computer vision pipeline to analyze machine drawings and reconstruct 3D models when direct image viewing was unavailable. Opus 5 improved at finding cybersecurity vulnerabilities through general capability gains rather than explicit training, while Anthropic deliberately avoided training it on exploitation techniques.
Anthropic released Claude Opus 5, replacing Claude Opus 4.8 at the same price of $5 per million input tokens and $25 per million output tokens. The model enables thinking by default (whereas Opus 4.8 required manual activation), supports up to 1 million token context with 128k output on the standard API, and requires developers to remove verification prompts from existing code since the model now self-verifies. Developers must update API calls to handle the new thinking behavior or explicitly disable it, and they can reduce prompt cache minimums from 1,024 to 512 tokens.
Anthropic released Opus 5, an updated language model focused on cost efficiency rather than major capability gains. The model performs at roughly the same level as Anthropic's Fable on coding benchmarks while costing approximately half as much, and shows only iterative improvements over Opus 4.8. Opus 5 deliberately lacks some cybersecurity training and drops certain safety policies, positioning it as a practical middle ground for developers prioritizing affordability over cutting-edge performance.
Anthropic released Opus 5, priced at $5 per million input tokens and $25 per million output tokens—one-third the cost of Fable 5—while achieving state-of-the-art results on coding benchmarks including OSWorld 2.0 and ARC-AGI 3. The lower cost enables longer autonomous agent execution, but creates new operational challenges around security, token spend control, and detecting when models fail to stop tasks. Platform teams must now implement microVMs, short-lived credentials, semantic circuit breakers, and better telemetry to safely deploy unsupervised AI agents that run unattended for hours.
Anthropic released Opus 5, a model that matches Fable 5's performance on many benchmarks while costing half as much, with pricing unchanged at $5/$25 per million tokens. On knowledge work benchmarks like GDPval-AA v2, Opus 5 scores 1861 compared to Fable 5's 1747, and it achieves double the pass rate of competing models on AutomationBench business workflow tasks. Opus 5 becomes the default model for Claude Max subscribers and shifts Fable 5's position as the company's tier for only the most demanding long-running autonomous projects.
Anthropic released Opus 5, a model smaller than its Fable 5 but cheaper and less restrictive while outperforming Fable 5 on several benchmarks. The model launched two months after Opus 4.8, and Anthropic reports its safety classifiers will engage 85% less often for Opus 5 than for Fable 5. Users now have access to a model with fewer restrictions and a new Automatic Fallbacks feature that routes blocked requests to a weaker model instead of returning an error.
Anthropic released Claude Opus 5, a new model that the company claims achieves capabilities close to Claude Fable 5 in many domains and shows significant improvements in complex coding tasks. Opus 5 arrives weeks after government scrutiny of Fable 5 led to a temporary takedown and the implementation of stronger cybersecurity measures. The release represents Anthropic's effort to provide a capable alternative following regulatory concerns about its most advanced model.
The Algorithmic Bridge·2 months ago·
12
● 75 sources
The White House accused Moonshot AI of stealing Anthropic's Fable model through large-scale distillation to develop its K3 model, with Treasury Secretary Scott Bessent warning that sanctions could follow. The accusation lacks supporting evidence, and the timeline doesn't align since Fable was only publicly available for two weeks before K3's release, making significant distillation implausible during training. The episode reveals divisions within the U.S. government and tech industry over whether to restrict Chinese AI models, while Chinese models already account for nearly 60% of token usage on OpenRouter by U.S. companies, making enforcement difficult and raising questions about America's confidence in competing through open-source alternatives rather than restrictions.
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