Anthropic Releases Claude Sonnet 5 at Lower Price Point
AI company Anthropic has launched its new Claude Sonnet 5 model, offering near flagship performance at a mid-tier price. The move aims to provide cost-conscious enterprise developers with advanced capabilities ahead of a potential IPO.

San Francisco – AI company Anthropic has launched its new Claude Sonnet 5 model, offering near flagship performance at a mid-tier price. The move aims to provide cost-conscious enterprise developers with advanced capabilities ahead of a potential IPO.
Sonnet 5 is now the default model for users on Anthropic's Free and Pro plans, and is also available to Max, Team, and Enterprise customers. Introductory API pricing is set at $2 per million input tokens and $10 per million output tokens through August 31. After this period, prices will rise to $3 and $15 respectively, still significantly below the $5 input and $25 output pricing of Anthropic's top-tier Opus 4.8 model.
The strategy is clear: Anthropic aims to democratize access to capabilities previously exclusive to its most expensive models. This move is designed to build broad developer adoption, which could be attractive for the company's upcoming initial public offering.
Performance benchmarks indicate that Sonnet 5 has significantly improved over its predecessor, Sonnet 4.6, in areas like coding and reasoning, narrowing the gap with Anthropic's flagship Opus model. For example, on the SWE-bench Pro test, Sonnet 5 achieved a score of 63.2%, approaching Opus 4.8's 69.2%.
The emphasis on "agentic capabilities"—the ability to plan, use tools, and execute multi-step workflows autonomously—reflects a key shift in the AI industry. Enterprises are increasingly seeking AI systems that can navigate complex environments and complete tasks with minimal human intervention. Early adopters have reported that Sonnet 5 can complete tasks that previous models struggled with, a crucial factor for moving AI solutions from pilot programs to full production. An updated tokenizer is also noted for performance gains, though its cost implications for specific workloads require careful evaluation.