Claude Sonnet 4.6 is positioned as a general-purpose large language model aimed squarely at engineering and coding-agent workloads, where Anthropic markets it as the strongest price-performance option in the family. The model retains the same pricing tier as its predecessor, at $3 per million input tokens and $15 per million output tokens, so teams can upgrade capability without renegotiating budgets. It is intended for messy, repository-scale problems rather than toy prompts, and the supporting evidence emphasizes real-world engineering tasks: long-horizon code fixes, terminal-driven agent loops, and multi-step tool use across real GitHub issues and shell environments.

On the engineering benchmarks that map to day-to-day agent work, Claude Sonnet 4.6 reports 79.6% on SWE-bench Verified, 59.1% on Terminal-Bench 2.0, and 72.5% on OSWorld-Verified, each an improvement over Sonnet 4.5, with the largest jump on the desktop computer-use suite at +11.1 points. These gains matter because the benchmarks reward planning, tool orchestration, and recovery from ambiguous instructions, not just single-turn answer quality. In practice, that translates into a model that fits well behind Snowflake Cortex for teams deploying coding assistants, automated refactoring agents, and data-platform workflows where the model must chain calls, read large contexts, and produce reliable code without constant hand-holding.