Anthropic Models

A strong workhorse balancing speed and intelligence: a 1M-token context window, text and image input, text output, adaptive thinking, and tool use for project-level coding, multi-step tasks, and knowledge work. Its main advantage over Sonnet 5 is faster, more token-efficient execution; choose Opus 5.5 when maximum quality for harder tasks matters more.

Built for long-running agentic coding and knowledge work, especially cross-file refactors, codebase audits, and complex multi-step tasks. Its 1M-token context, always-on adaptive thinking, and text/image input favor high-quality long-horizon execution; compared with Sonnet 5, it prioritizes depth at higher cost and latency.

A flagship long-context model for demanding, long-running knowledge work, coding projects, and multi-step agentic tasks. It accepts text, images, and PDFs, making it a strong fit for cross-file analysis, complex research, and sustained tool use. It prioritizes reasoning depth and long-horizon execution over speed and cost, so it is best reserved for tasks where reliable completion matters.

A premium model for complex agentic coding and enterprise knowledge work, emphasizing long-horizon planning, sustained execution, self-checking, and reliable delivery. With a million-token context window, it is suited to large codebases, complex documents, and multi-step projects that need limited human oversight.

Anthropic's most capable widely released model, built for the most demanding reasoning and long-horizon agentic work. Offers a 1M-token context window with 128k max output and always-on adaptive thinking, excelling at autonomously exploring underspecified tasks, planning, and carrying long-running coding and multi-agent orchestration further before it needs human input.

A daily-driver Sonnet-tier model aimed at bringing near-frontier agentic, coding, and knowledge-work capability at a lower operating cost. Its default 1M-token context and adaptive thinking fit long documents, codebases, and multi-step tool workflows; for the deepest reasoning or restricted high-risk security work, evaluate higher-tier or specialized models.

Anthropic current Opus flagship for the most demanding reasoning, long-running agents, and high-autonomy coding. It supports a 1M-token context window and adaptive thinking; choose it when quality and reliability matter more than latency or cost.

A high-capability Opus model for complex, long-running software engineering and agent tasks. Compared with Opus 4.6, it emphasizes precise instruction following, higher-resolution vision, sustained execution, and self-verification for large codebases, difficult debugging, document analysis, and multi-step tool use.

The Claude lineup workhorse, balancing strong intelligence, response speed, and cost. It supports a 1M-token context window and adaptive thinking, making it a strong starting point for coding, document analysis, data work, and tool-using agents; move to Opus for the most complex tasks.

An Opus model for demanding reasoning, agentic coding, and large-codebase work. Compared with Opus 4.5, it emphasizes longer-horizon planning, code review, debugging, autonomous execution, and document and spreadsheet work, with a 1M-token context window and adaptive thinking. Evaluate newer Opus 4.7 or 4.8 first for new projects.

An earlier Opus model in the Claude 4 family, focused on difficult coding, agents, computer use, deep research, and work with slides and spreadsheets. It fits workflows that require Opus-level capability with 4.5 compatibility; without that constraint, evaluate the newer Opus 4.6 or 4.7 first.

The fastest and more cost-efficient model in the Claude lineup, offering near-frontier capability with a 200K-token context window and thinking support. It fits real-time interaction, batch processing, lightweight agents, and cost-sensitive production; use Sonnet or Opus for the hardest reasoning or code changes.