Claude Sonnet 5 launches with 1M token context window, new tokenizer, and adaptive thinking enabled by default
Anthropic positions Sonnet 5 as nearly as capable as Opus 4.8 but at lower prices, while introducing a tokenizer that increases token counts by roughly 30% for many languages.
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- Claude Sonnet 5 is positioned by Anthropic as having performance close to Opus 4.8 at lower prices.
- The model features a 1 million token context window, 128,000 maximum output tokens, and adaptive thinking enabled by default.
- Sampling parameters temperature, top_p, and top_k are no longer supported.
- A new tokenizer increases token counts by approximately 30% for many languages, effectively raising costs despite unchanged list prices.
- Pricing remains $3 per million input tokens and $15 per million output tokens until August 31, with an introductory discount to $2/$10.
Anthropic released Claude Sonnet 5, positioning it as having performance close to Opus 4.8 but at lower prices, according to the developer documentation reviewed by Simon Willison. The company also released a system card explaining how the model’s safeguards compare to other releases.
The model introduces a 1 million token context window and supports up to 128,000 maximum output tokens. It retains the same set of tools and platform features as Claude Sonnet 4.6, but discontinues support for sampling parameters temperature, top_p, and top_k.
Adaptive thinking is enabled by default in Sonnet 5, unless developers explicitly disable it via the API. Anthropic’s pricing remains listed at $3 per million input tokens and $15 per million output tokens, with an introductory discount to $2/$10 until August 31.
A key change is the new tokenizer, which produces approximately 30% more tokens for the same input text compared to Claude Sonnet 4.6. This effectively increases costs by the same proportion despite unchanged list prices. Measurements across sample documents show roughly 1.4x more tokens for English, 1.33x for Spanish, 1.28x for Python code, and effectively no change for Simplified Mandarin.
Simon Willison used his Claude Token Counter tool to compare token counts across documents, including the Universal Declaration of Human Rights in English, Spanish, and Simplified Mandarin, as well as a 4,279-line Python file. The results confirm the approximately 30% increase in token counts for most languages tested.
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