MODEL DETAILS / anthropic/opus-5.1

opus-5.1

Introducing Opus-5.1, the latest breakthrough in large-scale language modeling. Built on a massive 5-trillion-parameter architecture, Opus-5.1 represents a generational leap in capability and efficiency. Trained on an unprecedented corpus of high-quality data spanning scientific literature, multilingual text, code repositories, and mathematical reasoning, the 5T parameter count enables it to handle deeply nuanced tasks smaller models cannot approach. From complex legal analysis to large-scale codebase comprehension, Opus-5.1 delivers state-of-the-art performance. What truly sets it apart is dramatically improved cost efficiency. Through novel sparse mixture-of-experts routing, advanced quantization-aware training, and a redesigned inference engine optimized for modern hardware, Opus-5.1 achieves roughly 40 percent lower per-token inference costs compared to its predecessor, despite the massive parameter increase. This allows organizations to deploy frontier-level intelligence at a fraction of the operational expense, making it viable for high-throughput production workloads. The model supports a context window of up to 1 million tokens, enabling it to ingest and reason over entire books or massive datasets in a single pass. Its instruction-following capabilities are refined through a multi-stage alignment pipeline incorporating human preference optimization and rigorous red-teaming, ensuring outputs are accurate, safe, and helpful. Opus-5.1 also introduces improved tool-use orchestration, seamlessly chaining API calls and external computations within a single reasoning trace. With multilingual fluency across 120+ languages and code generation rivaling dedicated models, Opus-5.1 is designed for teams demanding the highest AI performance without sacrificing budget predictability. It is the new standard for efficient, frontier AI.

Model metadata is served from the local cache (updated 2026-11-11).