Claude Sonnet 4.5 (latest)

Claude 4.5 Sonnet is a dense transformer-based model engineered to balance high-order reasoning with operational efficiency. It features a hybrid reasoning system that allows users to toggle between a low-latency mode for rapid interactions and an extended thinking mode for tackling difficult, multi-step problems. Built with absolute position embeddings and multi-head attention, the model is designed to maintain stability and accuracy across long sequences, making it a robust choice for autonomous systems and professional environments that require reliable instruction following.

The model benefits from advanced training methodologies, including reinforcement learning from human feedback and constitutional AI techniques, which refine its alignment and performance. These training approaches contribute to its strong results in coding, language understanding, and reasoning benchmarks. By supporting both standard and extended context capacities, the model is well-suited for processing massive datasets and entire codebases, positioning it as a versatile tool for developers and researchers who need a dependable, high-capacity engine for complex, long-running workflows.