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Amazon - Amazon Bedrock

Amazon

The following Amazon models are available in Amazon Bedrock:

Model Description
Nova 2 LiteNova 2 Lite is Amazon's cost-efficient multimodal model for simple automation, document processing, and customer support across text, images, and video.
Nova 2 SonicNova 2 Sonic is Amazon's speech-to-speech foundation model for building natural, real-time voice conversation applications.
Nova LiteNova Lite is Amazon's low-cost multimodal model that processes text, images, and video inputs for tasks like document analysis and visual Q&A.
Nova MicroNova Micro is Amazon's fastest text-only model, optimized for speed and low cost in tasks like summarization, translation, and classification.
Nova ProNova Pro is Amazon's balanced multimodal model offering strong accuracy, speed, and cost for a wide range of tasks across text, images, and video.
Amazon Nova Multimodal EmbeddingsAmazon Nova Multimodal Embeddings is Amazon's embedding model that converts text, images, and video into vector representations for search and retrieval use cases.
Nova CanvasNova Canvas is Amazon's image generation model that creates studio-quality images from text and image prompts with built-in controls for watermarking and content moderation.
Nova ReelNova Reel is Amazon's video generation model that creates short videos from text and image prompts with camera motion controls.
Titan Text Embeddings V2Titan Text Embeddings V2 is Amazon's second-generation text embeddings model with configurable output dimensions and improved accuracy for retrieval tasks.
Titan Multimodal Embeddings G1Titan Multimodal Embeddings G1 is Amazon's model that generates embeddings from text and images for multimodal search and recommendation use cases.
Titan Embeddings G1 - TextTitan Text Embeddings G1 is Amazon's text embeddings model that converts text into numerical vector representations for search, personalization, and clustering.
Titan Embeddings G1 - Text v2Titan Text Embeddings V2:2 is an updated version of Amazon's text embeddings model with configurable output dimensions and improved accuracy for retrieval tasks.