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Claude 3.5 Sonnet
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About

Claude 3.5 Sonnet is a versatile generative AI tuned for creative writing, advanced coding, visual reasoning, and autonomous multi-step workflows. Built for enterprises and developers and available via platforms such as Yale’s Clarity, Amazon Bedrock, Vertex AI, and Claude.ai, Sonnet helps teams prototype software, migrate legacy code, draft polished content, and extract insights from images and mixed data. Its improved software engineering performance (SWE-bench Verified rising from 33% to 49%) and benchmark gains on domain tests make it one of the leading public models for practical coding tasks. Sonnet can write, edit, and execute code to accelerate development cycles, support debugging, and generate working functions from high-level specifications. Its vision capabilities interpret charts, diagrams, and imperfect images reliably, enabling better business intelligence in retail, logistics, and finance. Unique tool-integration training enables Sonnet to interact with software interfaces and perform web navigation and multi-step workflows autonomously where platform integrations allow. On Claude.ai, the Artifacts workspace supports collaborative creation and iterative editing of code, documents, and other assets in real time. The model also excels at complex customer support, orchestrating multi-stage resolutions, and producing statistical visualizations and actionable analysis from unstructured data. Operationally, Sonnet delivers lower latency and stronger instruction following than prior versions while maintaining the same price and speed. It underwent safety evaluations by U.S. and U.K. AI safety institutes and follows responsible scaling practices. Limitations include restricted file-upload support on some platforms, non-recommendation for processing ePHI, and the need for human oversight for mission-critical or highly specialized tasks. For teams seeking a high-performance assistant that bridges creative, analytical, and engineering workflows, Claude 3.5 Sonnet offers a powerful, practical, and collaborative solution.

Percs

Fast generation
Multi-modal
High quality
High accuracy

Settings

Diversity control (Top P)-  Filters AI responses based on probability.
Lower values = top few likely responses,
Higher values = larger pool of options.
Temperature-  The temperature of the model. Higher values make the model more creative and lower values make it more focused.
Response length-  The maximum number of tokens to generate in the output.
Context length-  The maximum number of tokens to use as input for a model.