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Amazon Bedrock

AWS managed service for building and scaling generative AI applications using foundation models from leading AI companies.

Starting at$0.25 per 1M input tokens / $1.25 per 1M output tokens
Visit Amazon Bedrock →
OverviewFeaturesPricingUse CasesLimitationsFAQSecurityAlternatives

Overview

Amazon Bedrock is an AI Platform managed service that provides access to hundreds of foundation models from leading AI companies for building and scaling generative AI applications and agents in production, with pay-as-you-go pricing and up to $200 in AWS credits for new customers. It targets enterprises, startups, and developers who need production-grade infrastructure with enterprise security, compliance, and flexibility.

Used by more than 100,000 organizations worldwide across every industry, Amazon Bedrock unifies the core capabilities needed to move generative AI from prototype to production. The platform provides access to hundreds of foundation models from providers like Anthropic, Meta, Mistral, Cohere, Stability AI, and Amazon's own Nova models, along with evaluation tools to help teams select the best model for specific cost and performance needs. Customization features include Knowledge Bases for retrieval-augmented generation, Bedrock Data Automation, prompt engineering, and fine-tuning—allowing teams to move from generic AI to models that understand their specific business context without exposing sensitive data.

Bedrock's differentiator is its AgentCore platform, a composable suite for deploying agents securely at scale without infrastructure management. AgentCore includes Runtime for serverless deployment, Gateway for tool access, Memory for context retention, Identity for authentication, Browser and Code Interpreter capabilities, Observability for monitoring, Evaluations for quality scoring, and Policy for fine-grained control. Cost optimization features like Model Distillation deliver up to 500% faster inference and 75% cost reduction, while Intelligent Prompt Routing cuts costs by up to 30%. Bedrock Guardrails block up to 88% of harmful content and achieve up to 99% accuracy in identifying correct model responses via Automated Reasoning checks.

Compared to the other AI platforms in our directory, Amazon Bedrock stands out for enterprises already invested in AWS. Based on our analysis of 870+ AI tools, competitors like Google Vertex AI and Azure AI Foundry offer similar multi-model access, but Bedrock's tight integration with AWS IAM, VPC, CloudWatch, and compliance certifications (ISO, SOC, CSA STAR Level 2, GDPR, FedRAMP High, HIPAA-eligible) make it the default choice for regulated industries. Robinhood, for instance, scaled from 500 million to 5 billion daily tokens on Bedrock while cutting AI costs by 80%.

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Key Features

Multi-model access via a single API+

Bedrock gives you one unified API to invoke hundreds of foundation models from Anthropic, Meta, Mistral, Cohere, Stability AI, AI21, and Amazon. This means you can swap models as new ones emerge or route different workloads to different models without rewriting application code, future-proofing your AI strategy.

AgentCore agentic platform+

AgentCore is a composable set of nine services—Runtime, Gateway, Memory, Identity, Browser, Code Interpreter, Observability, Evaluations, and Policy—for running agents securely at production scale. Services work together or independently, and agents can be built with any framework, so you are not locked into a specific agent SDK or orchestration tool.

Guardrails and Automated Reasoning checks+

Bedrock Guardrails block up to 88% of harmful content through configurable content filters, denied topics, and sensitive-information filters. Automated Reasoning checks use formal verification to confirm model responses are correct with up to 99% accuracy—a differentiating safety layer most competitors don't offer.

Customization via Knowledge Bases and fine-tuning+

Knowledge Bases provide managed RAG over your proprietary data, automatically handling chunking, embeddings, and vector storage. Combined with Bedrock Data Automation for multimodal ingestion, prompt engineering tools, and managed fine-tuning, teams can adapt foundation models to business-specific context without exposing sensitive data to third-party providers.

Cost-optimization primitives+

Model Distillation trains smaller student models that run up to 500% faster and cost up to 75% less with minimal accuracy loss. Intelligent Prompt Routing automatically sends each prompt to the most cost-effective model that can handle it, cutting costs by up to 30%. Prompt caching and batch inference further reduce spend for recurring workloads.

Pricing Plans

Claude Haiku (Anthropic)

$0.25 per 1M input tokens / $1.25 per 1M output tokens

  • ✓Lightweight, fast model for high-volume tasks
  • ✓On-demand pay-per-token pricing
  • ✓Suitable for classification, extraction, and simple Q&A
  • ✓Lowest-cost Anthropic option on Bedrock

Claude Sonnet (Anthropic)

$3.00 per 1M input tokens / $15.00 per 1M output tokens

  • ✓Balanced performance and cost for most production workloads
  • ✓Strong reasoning and coding capabilities
  • ✓On-demand pay-per-token pricing
  • ✓200K context window

Claude Opus (Anthropic)

$15.00 per 1M input tokens / $75.00 per 1M output tokens

  • ✓Frontier-class model for complex reasoning and analysis
  • ✓Highest accuracy on demanding benchmarks
  • ✓On-demand pay-per-token pricing
  • ✓Best for tasks requiring deep expertise

Llama 3.1 8B (Meta)

$0.22 per 1M input tokens / $0.22 per 1M output tokens

  • ✓Open-weight small model at very low cost
  • ✓128K context window
  • ✓On-demand pay-per-token pricing
  • ✓Good for lightweight inference and high-throughput pipelines

Llama 3.1 70B (Meta)

$0.99 per 1M input tokens / $0.99 per 1M output tokens

  • ✓Mid-tier open-weight model with strong general performance
  • ✓128K context window
  • ✓On-demand pay-per-token pricing
  • ✓Cost-effective alternative to proprietary mid-range models

Amazon Nova Micro

$0.035 per 1M input tokens / $0.14 per 1M output tokens

  • ✓Amazon's lowest-cost text model
  • ✓Optimized for speed and simple tasks
  • ✓On-demand pay-per-token pricing
  • ✓Ideal for high-volume, latency-sensitive workloads

Amazon Nova Pro

$0.80 per 1M input tokens / $3.20 per 1M output tokens

  • ✓Multimodal model supporting text, images, and video
  • ✓Balanced accuracy, speed, and cost
  • ✓On-demand pay-per-token pricing
  • ✓300K context window

Mistral Large

$4.00 per 1M input tokens / $12.00 per 1M output tokens

  • ✓Frontier-class model from Mistral AI
  • ✓Strong multilingual and coding performance
  • ✓On-demand pay-per-token pricing
  • ✓128K context window

New Customer Credits

Up to $200 in free AWS credits

  • ✓Available to new AWS customers for trying AI services
  • ✓Applies across Bedrock model inference
  • ✓No long-term commitment required
  • ✓Credits expire after a limited period
See Full Pricing →Free vs Paid →Is it worth it? →

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Best Use Cases

🎯

Regulated enterprises (finance, healthcare, government) building generative AI applications that must meet FedRAMP High, HIPAA, or SOC compliance requirements while retaining data sovereignty

⚡

Engineering teams deploying production AI agents that need enterprise authentication, tool access, and observability without building infrastructure from scratch—using AgentCore's composable services

🔧

Organizations requiring multi-model flexibility so they can evaluate and swap between Claude, Llama, Mistral, and Amazon Nova models without rewriting application code or renegotiating vendor contracts

🚀

Customer service and virtual assistant applications that combine foundation models with Knowledge Bases for RAG over internal documentation, product catalogs, or support tickets

💡

High-volume workloads where cost matters: use Model Distillation to create smaller, faster custom models and Intelligent Prompt Routing to automatically send simpler queries to cheaper models

🔄

Marketing and content operations (like Epsilon's use case) where agents automate complex campaign workflows, from audience segmentation to personalized content generation across millions of customers

Limitations & What It Can't Do

We believe in transparent reviews. Here's what Amazon Bedrock doesn't handle well:

  • ⚠Requires an AWS account and working knowledge of the AWS ecosystem—not ideal for teams that want a standalone, provider-agnostic AI platform
  • ⚠Foundation model availability differs by AWS region, so some models may not be accessible in the regions where your workloads run
  • ⚠Managed layer adds latency overhead compared to calling model provider APIs directly, which can matter for latency-critical applications
  • ⚠Total cost of ownership can be difficult to forecast because inference, AgentCore, Guardrails, Knowledge Bases, and data transfer each appear as separate line items
  • ⚠Custom model import and fine-tuning workflows still require ML expertise to tune hyperparameters, evaluate results, and manage model versions over time

Pros & Cons

✓ Pros

  • ✓Trusted by over 100,000 organizations worldwide, including regulated industries like fintech (Robinhood) and healthcare
  • ✓Single API access to hundreds of foundation models from Anthropic, Meta, Mistral, Cohere, Amazon, and others—no vendor lock-in to one model
  • ✓Industry-leading compliance posture (FedRAMP High, HIPAA-eligible, SOC, ISO, GDPR) makes it viable for regulated workloads where competitors fall short
  • ✓AgentCore removes the infrastructure burden of running agents at scale—Epsilon shrank agent development from months to weeks
  • ✓Cost optimization tools are concrete and measurable: Model Distillation cuts costs up to 75%, Intelligent Prompt Routing up to 30%, with prompt caching layered on top
  • ✓Bedrock never stores or uses customer data to train models, with encryption at rest and in transit plus identity-based access policies

✗ Cons

  • ✗Pricing complexity is steep—per-token costs vary by model, and add-ons like AgentCore, Guardrails, and Knowledge Bases each bill separately
  • ✗Steep learning curve for teams not already familiar with AWS IAM, VPC networking, and CloudWatch monitoring
  • ✗No free tier beyond the $200 new-customer credits; ongoing usage requires active AWS billing from day one
  • ✗Model availability varies by AWS region, which can complicate global deployments and force architectural compromises
  • ✗Latency can be higher than going direct to model providers like OpenAI or Anthropic, since Bedrock adds a managed layer in front of the underlying APIs

Frequently Asked Questions

Which foundation models are available on Amazon Bedrock?+

Amazon Bedrock provides access to hundreds of foundation models from leading AI companies, including Anthropic's Claude family, Meta's Llama, Mistral, Cohere, Stability AI, AI21 Labs, and Amazon's own Nova and Titan models. The model catalog expands regularly as new models are released, and built-in evaluation tools let you benchmark options against your specific use case. You can also import custom fine-tuned models, giving you flexibility to combine proprietary and third-party models in the same application.

How does Amazon Bedrock handle data privacy and security?+

Bedrock never stores or uses your data to train the underlying foundation models, and all data is encrypted in transit and at rest. Access is governed by AWS IAM identity-based policies, and traffic can be kept private using VPC endpoints. Bedrock is in scope for ISO, SOC, CSA STAR Level 2, GDPR, and FedRAMP High compliance, and is HIPAA eligible—making it one of the few generative AI platforms approved for regulated industries like healthcare, financial services, and government.

What is Amazon Bedrock AgentCore and how is it different from Bedrock Agents?+

AgentCore is a composable agentic platform that lets you build, deploy, and operate agents at production scale using any framework or model without managing infrastructure. It includes nine independent services: Runtime, Gateway, Memory, Identity, Browser, Code Interpreter, Observability, Evaluations, and Policy. Bedrock Agents is the higher-level, guided agent-building experience, while AgentCore gives more advanced teams lower-level primitives to compose custom agentic architectures, including agents that interact with third-party tools and data sources.

How much does Amazon Bedrock cost?+

Amazon Bedrock uses pay-as-you-go pricing based primarily on input and output tokens, with rates varying by model—so a call to a frontier model like Claude Opus costs more than a smaller model like Claude Haiku or Llama. Additional features including AgentCore services, Knowledge Bases, Guardrails, Model Distillation, and fine-tuning are billed separately. New AWS customers receive up to $200 in AWS credits to try AWS AI for free, and cost-optimization features like Intelligent Prompt Routing and prompt caching can cut inference bills by 30% or more.

How does Amazon Bedrock reduce hallucinations and unsafe outputs?+

Bedrock Guardrails can block up to 88% of harmful content via configurable content filters, denied topics, word filters, sensitive-information filters, and contextual grounding checks. For factual accuracy, Automated Reasoning checks use formal mathematical verification to identify correct model responses with up to 99% accuracy—a capability most competitors do not offer. Combined with Knowledge Bases for grounding responses in your proprietary data and Bedrock's evaluation tools, you can systematically reduce hallucinations and enforce safety policies in production.
🦞

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What's New in 2026

Amazon Bedrock AgentCore is positioned as the flagship 2025-2026 capability, offering a composable agentic platform (Runtime, Gateway, Memory, Identity, Browser, Code Interpreter, Observability, Evaluations, Policy) for deploying agents at production scale without infrastructure management. Customers like Epsilon are using AgentCore to compress agent development from months to weeks, and Bedrock now powers generative AI for more than 100,000 organizations worldwide. Automated Reasoning checks have matured to deliver up to 99% accuracy for identifying correct model responses, and Intelligent Prompt Routing and Model Distillation are highlighted as key cost-reduction features for 2026 workloads.

Alternatives to Amazon Bedrock

Google Vertex AI

AI Platform

Google Cloud's unified platform for machine learning and generative AI, offering 180+ foundation models, custom training, and enterprise MLOps tools.

Databricks Mosaic AI Agent Framework

Agent Platforms

Automated enterprise AI agent platform that builds production-grade agents optimized for your business data. Features four specialized agent types with automatic optimization, synthetic data generation, and built-in governance for rapid deployment from concept to production.

View All Alternatives & Detailed Comparison →

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