Claude Sonnet 4.6

Claude Sonnet 4.6 is an AI model verified from first-party Anthropic sources.

Claude Sonnet 4.6 verified specifications

Claude Sonnet 4.6 is Anthropic’s active legacy balanced model with 1M context, 128K output, vision and adaptive reasoning for coding and everyday agent tasks. Its verified context or usage limit is 1000000 tokens, with 128000 tokens maximum output.

Claude Sonnet 4.6 pricing and access

Claude Sonnet 4.6 costs $3 per 1M input tokens and $15 per 1M output tokens. Batch API processing is discounted by 50%.

Claude Sonnet 4.6 best uses

Coding, General agents, Long-context documents, Research, Professional knowledge work.

Claude Sonnet 4.6 limitations

Anthropic recommends Sonnet 5, Older tokenizer than newer Claude generations, Outputs still require validation.

Claude Sonnet 4.6 capabilities and use cases

In addition, its main capabilities include 1M context, 128K output, Adaptive thinking, Vision, Tool use and Batch output up to 300K beta. For example, common use cases include Coding, Agents, Research, Document intelligence and Professional assistants.

Who should consider Claude Sonnet 4.6?

In practice, this model may suit Coding, General agents, Long-context documents, Research and Professional knowledge work. Also, notable strengths include Strong balance of speed and capability, 1M context and Broad cloud support. However, review trade-offs such as Anthropic recommends Sonnet 5, Older tokenizer than newer Claude generations and Outputs still require validation before adopting it.

Claude Sonnet 4.6 pricing and access

Meanwhile, Claude Sonnet 4.6 costs $3 per 1M input tokens and $15 per 1M output tokens. Batch API processing is discounted by 50%. Base pricing is $3/M input and $15/M output; Anthropic now recommends Sonnet 5 for new integrations.

Official resources and verification

Use the official model website, official documentation, pricing or release source and additional primary source to confirm current availability, limits and pricing. Product details can change after publication, so rely on primary documentation for final decisions.

Compare with other AI models

Next, continue your research in the AI models directory, Anthropic models and General Purpose Language Model models. Compare providers, pricing, modalities and practical limitations side by side to choose the right model for your workflow.