Claude 4 Sonnet
Claude Sonnet 4 is Anthropic's efficient and capable mid-tier model, delivering state-of-the-art coding and reasoning performance at scale.
Anthropic Efficient mid-tier model for coding and reasoning
Claude Sonnet 4 (claude-sonnet-4-20250514) is a text generation model developed by Anthropic and released on May 22, 2025. It sits in the mid-tier of Anthropic's Claude 4 model family, designed to balance capability with computational efficiency for production use. The model supports a 200,000-token context window and accepts text, images, and PDFs as input. It includes an optional extended thinking mode that allows the model to perform step-by-step reasoning when tasks require greater depth.
Claude Sonnet 4 is built for high-volume workloads where consistent performance and reliability matter. It scores 72.7% on SWE-bench, reflecting strong performance on software engineering tasks such as code generation, debugging, and codebase navigation. The model also supports agentic tool use, making it suitable for multi-step workflows and integration with external APIs. Common use cases include code review, customer support automation, data analysis, and long-document processing.
What Claude 4 Sonnet supports
Hybrid Reasoning
Supports both standard fast responses and an optional extended thinking mode that works through problems step by step, adapting reasoning depth to task complexity.
Code Generation
Handles code generation, debugging, refactoring, and autonomous codebase navigation, achieving a 72.7% score on the SWE-bench benchmark.
Large Context Window
Processes up to 200,000 tokens in a single context, enabling analysis of large codebases, lengthy documents, and extended multi-turn conversations.
Vision & Multimodal Input
Accepts images and PDFs alongside text, allowing the model to analyze visual content and documents within the same request.
Agentic Tool Use
Supports tool calling and multi-step workflows, enabling integration with external APIs and use as a subagent in complex AI pipelines.
Configurable Parameters
Exposes numeric configuration options such as temperature and token limits, giving developers fine-grained control over output behavior.
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Get Started FreeBenchmark scores
Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Score |
|---|---|---|
| MMLU-Pro | Expert knowledge across 14 academic disciplines | 83.7% |
| GPQA Diamond | PhD-level science questions (biology, physics, chemistry) | 68.3% |
| MATH-500 | Undergraduate and competition-level math problems | 93.4% |
| AIME 2024 | American math olympiad problems | 40.7% |
| LiveCodeBench | Real-world coding tasks from recent competitions | 44.9% |
| HLE | Questions that challenge frontier models across many domains | 4.0% |
| SciCode | Scientific research coding and numerical methods | 37.3% |
Common questions about Claude 4 Sonnet
What is the context window size for Claude Sonnet 4?
Claude Sonnet 4 supports a context window of 200,000 tokens, which allows it to process large documents, long conversation histories, and extensive codebases in a single request.
What is the knowledge cutoff date for Claude Sonnet 4?
The model's training data has a cutoff of May 2025, as indicated in the model metadata.
What input types does Claude Sonnet 4 support?
Claude Sonnet 4 accepts text, images, and PDFs as input, making it capable of handling both natural language and visual or document-based content.
Does Claude Sonnet 4 support tool use and agentic workflows?
Yes. Claude Sonnet 4 is built to support tool calling, multi-step task execution, and integration with external APIs, making it suitable for use as an agent or subagent in automated pipelines.
What is the model identifier for Claude Sonnet 4?
The full model identifier is claude-sonnet-4-20250514. This is the version string used when calling the model via Anthropic's API.
What people think about Claude 4 Sonnet
Community discussions around Claude Sonnet 4's release were largely positive, with users on r/ClaudeAI expressing enthusiasm about the model's availability and coding capabilities. Several threads highlighted its performance on software engineering tasks as a notable aspect of the release.
Some users raised questions about pricing relative to competing models, with at least one thread debating whether the cost of Anthropic's models is justified compared to alternatives. Coding assistance, agentic workflows, and production-scale use cases appear to be the most commonly discussed applications.
Compared Claude 4 Sonnet and Opus against Gemini 2.5 Flash. There is no justification to pay 10x to OpenAI/Anthropic anymore
New benchmark: Claude Opus 4.5 broke the efficiency wall.+21% intelligence while getting 66% cheaper
Claude delivers finally opus can't stop this excitement
Claude 4 Sonnet and Opus Coming Soon
Deepseek is the 4th most intelligent AI in the world.
Documentation & links
Parameters & options
When enabled, the model will explain its thought process step-by-step before providing a final answer. This can help users understand how the model arrived at its conclusions, but may result in longer responses.
You can allocate a larger thinking budget to support more thorough reasoning. Must be less than max. response size
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