Amazon Bedrock handles different generative AI modalities, like text and image generation, by providing access to specialized foundation models through a unified API. Each modality is managed by distinct models optimized for their specific tasks. For example, text generation might use models like Anthropic’s Claude or Amazon Titan, while image generation could leverage Stability AI’s Stable Diffusion. Bedrock abstracts the infrastructure complexity, letting developers interact with these models via standardized endpoints without managing the underlying servers or scaling.
For text generation, models process input prompts and generate outputs by predicting sequences of tokens. A developer might send a JSON payload containing a prompt and parameters like temperature or max tokens. The model returns generated text, which could be anything from code snippets to marketing copy. For instance, using Claude via Bedrock, a developer could automate customer support responses by feeding user queries into the model and receiving structured replies. Image models work differently: they accept text prompts and sometimes seed images, outputting pixel arrays or image URLs. A developer might request a 512x512 product image from Stable Diffusion by specifying style parameters and receiving a base64-encoded image. Bedrock’s API standardizes these interactions, though the input formats and output structures vary between text and image models.
The service manages scalability and optimization behind the scenes. Text models typically handle higher throughput with lower latency, while image generation requires more computational resources per request. Bedrock allows developers to control costs through configurable parameters—like limiting image resolution or capping text response length. For example, a developer could choose Amazon Titan for text summarization at $0.001 per 1k tokens, while using Stable Diffusion for image generation at $0.02 per image. Bedrock’s model catalog clarifies each option’s capabilities, letting teams mix modalities in applications—like generating product descriptions alongside matching visuals—without infrastructure overhead.