Amazon Bedrock Verified listing

Amazon Bedrock - Build and Scale Generative AI Applications

Amazon Bedrock is a fully managed service offering a selection of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon. It enables users to build generative AI applications with security, privacy, and responsible AI practices.

Key Features

• Model Choice: Access a variety of FMs via a single API, enabling flexibility and easy upgrades.
• Customization: Privately fine-tune models with your data using techniques like Retrieval Augmented Generation (RAG).
• Security and Privacy: Robust features to secure data and applications.
• Safety Guardrails: Tools to build generative AI applications safely and responsibly.

Foundation Models

• Amazon Titan: Text and image generation, summarization, classification, Q&A, information extraction, and search.
• Claude: Dialogue, content creation, reasoning, creative writing, and coding.
• Command and Embed: Text generation and representation for various tasks including RAG.
• Jurassic: Enterprise-level instruction-following FMs for multiple text tasks.
• Llama: Models for dialogue and natural language tasks.
• Mistral AI: Text summarization, classification, completion, and code generation.
• Stable Diffusion: Image generation for visuals, art, logos, and designs.

Amazon Bedrock Pricing

Pricing varies by model provider and region. Here are some examples:

• AI21 Labs: $0.0125 per 1,000 input/output tokens for Jurassic-2 Mid model.
• Anthropic: $0.0008 per 1,000 input tokens and $0.0024 per 1,000 output tokens for Claude Instant.
• Cohere: $0.0015 per 1,000 input tokens and $0.0020 per 1,000 output tokens for Command model.
• Stability AI: $0.018 per image for standard quality (512x512 or smaller).

Pros and Cons

Pros:

• Wide selection of high-performing models.
• Flexible pricing options.
• Easy integration with existing AWS services.
• Strong security and privacy features.
• Serverless infrastructure reduces management overhead.

Cons:

• Costs can add up with high usage.
• Customization requires a commitment to Provisioned Throughput.
• Complex pricing structure may be difficult to navigate.