Claude Sonnet 4.5

Product Introduction

1. Claude Sonnet 4.5 is an advanced AI model designed for building complex autonomous agents, excelling in coding, computer interaction, and multi-step problem-solving. It represents Anthropic’s state-of-the-art release, offering substantial improvements in reasoning, mathematics, and tool utilization compared to previous models. The model integrates directly with development environments and productivity tools, enabling seamless automation of software development, data analysis, and workflow optimization.
2. The core value of Claude Sonnet 4.5 lies in its ability to handle long-horizon tasks with precision, maintaining focus for over 30 hours on intricate workflows while reducing human intervention. It is engineered to bridge the gap between AI capabilities and real-world productivity, particularly in domains requiring deep technical expertise like finance, law, medicine, and STEM.

Main Features

1. Claude Sonnet 4.5 achieves a 77.2% success rate on the SWE-bench Verified evaluation, making it the world’s leading coding model for real-world software engineering tasks. It supports parallel tool execution, such as running multiple bash commands simultaneously, and integrates natively with VS Code via an extension for direct codebase interaction.
2. The model demonstrates a 61.4% performance on the OSWorld benchmark, outperforming previous models by 19.2 percentage points in real-world computer tasks like browser navigation, spreadsheet automation, and document creation. It includes checkpoints for progress saving and rollbacks, along with a memory tool for managing context across extended agentic workflows.
3. Claude Sonnet 4.5 shows a 44% reduction in vulnerability intake time and a 25% accuracy improvement in security applications, enabled by enhanced reasoning and domain-specific knowledge. It operates within a 200K–1M token context window, with extended thinking budgets up to 128K tokens for complex problem-solving in finance, legal analysis, and scientific research.

Problems Solved

1. The model addresses the challenge of maintaining coherence in long-running, multi-step tasks, such as debugging large codebases or analyzing litigation records spanning thousands of pages. It reduces manual effort in code testing, vulnerability detection, and architectural planning by automating iterative processes.
2. Target users include developers building AI-powered tools, enterprises in regulated industries (e.g., finance, healthcare), and professionals requiring high-accuracy domain expertise. Early adopters span GitHub Copilot integrators, cybersecurity teams, and legal tech platforms like CoCounsel.
3. Typical use cases include generating production-ready code with integrated testing, synthesizing legal briefs from case law, automating financial portfolio analysis, and creating functional prototypes in design tools like Figma. It also powers red teaming scenarios for cybersecurity threat modeling.

Unique Advantages

1. Unlike competitors, Claude Sonnet 4.5 combines 30+ hours of autonomous task persistence with ASL-3 safety protocols, reducing sycophancy and power-seeking behaviors by 40% compared to Claude Opus 4.1. It achieves this while maintaining a 12% higher accuracy than GPT-5 on Terminal-Bench evaluations for CLI-based workflows.
2. The Claude Agent SDK provides infrastructure for custom agent development, including subagent coordination and permission systems tested in Anthropic’s own products. This allows developers to replicate Claude Code’s capabilities in niche applications without starting from scratch.
3. Competitive advantages include native integration with Chrome for browser automation, real-time code generation via the "Imagine with Claude" research preview, and a 0% error rate on internal code-editing benchmarks. The model’s CBRN risk classifiers have reduced false positives by 10x since initial deployment.

Frequently Asked Questions (FAQ)

1. How does Claude Sonnet 4.5 compare to Claude Sonnet 4? Claude Sonnet 4.5 improves SWE-bench performance by 35 percentage points, extends context handling to 1M tokens, and reduces code-editing errors from 9% to 0%. It introduces the Claude Agent SDK and VS Code extension, unavailable in previous versions.
2. Can Claude Sonnet 4.5 handle 30+ hour coding tasks reliably? Yes, the model uses checkpoints and a memory tool to maintain state across extended sessions, with validation showing 82% success on high-compute SWE-bench configurations using parallel sampling and test rejection techniques.
3. What security measures protect against prompt injection attacks? Anthropic implements ASL-3 safeguards, including input/output classifiers for CBRN risks and a fallback to Claude Sonnet 4 for flagged conversations. The system card details anti-sycophancy training and mechanistic interpretability audits.
4. How do developers access the Claude Agent SDK? The SDK is available immediately via Anthropic’s API, using the claude-sonnet-4-5 model identifier. It includes prebuilt modules for subagent coordination, memory management, and permission systems identical to those in Claude Code.
5. Is Claude Sonnet 4.5 compatible with existing GitHub Copilot integrations? Yes, early evaluations show 18% better planning performance and 12% higher end-to-end scores in Copilot workflows, particularly for codebase-spanning tasks requiring multi-repository analysis.