Supported models

This table shows the LLMs that are available within the GenAI application:
Provider Name Description Token Window
Anthropic Claude 3 Haiku Fast and compact model for near-instant responsiveness. Can answer simple queries and requests with speed as a priority. 200,000
Anthropic Claude3.5 Haiku (deprecating in June 2026) Fast and compact model for near-instant responsiveness. Can answer simple queries and requests with considerable speed. 200,000
Anthropic Claude Haiku 4.5 Delivers near-frontier performance for a wide range of use cases and stands out as one of the best coding and agent models–with the right speed and cost to power free products and high-volume user experiences. 200,000
Anthropic Claude 3.5 Sonnet(deprecated March 1, 2026) Twice the speed of Claude 3 Opus, ideal model for complex workflows within a cost-effective pricing. 200,000
Anthropic Claude 3.7 Sonnet (deprecated April 28, 2026) Anthropic's most intelligent model to date and the first Claude model to offer extended thinking, that is the ability to solve complex problems with careful, step-by-step reasoning. 128,000
Anthropic Claude Sonnet 4 Claude Sonnet 4 balances performance for coding with the right speed and cost for high-volume use cases. 200,000
Anthropic Claude Sonnet 4.5 Sonnet 4.5 is Claude's most capable model to date for building real-world agents and handling complex, long-horizon tasks–balancing the right speed and cost for high-volume use cases. 200,000
Meta Llama 3 8B Ideal for limited computational power and resources, edge devices, and faster training times. 8,192
Meta Llama 3 70B Ideal for content creation, conversational AI, language understanding, R&D, and Enterprise applications. 8,192
Amazon Nova Micro Text-to-text understanding foundation model. Model that is multilingual and can reason over text. 128,000
Amazon Nova Lite A multimodal understanding foundation model that can reason over text, images, and videos. 300,000
Amazon Nova Pro High capacity for enterprise-level computations that performs effectively in a large variety of tasks. 300,000