AWS Bedrock Pricing Calculator

What Is AWS Bedrock Pricing

Amazon Bedrock is AWS's fully managed service for accessing foundation models from leading AI providers — including Anthropic (Claude), Meta (Llama), Amazon (Titan), Mistral, Cohere, and Stability AI. Bedrock pricing varies significantly by model, input/output token counts, and whether you use on-demand or provisioned throughput, making cost estimation essential before deploying AI workloads.

This calculator helps you estimate Bedrock costs based on your expected usage patterns, model selection, and throughput requirements — enabling informed decisions about model selection and deployment strategy.

Bedrock Pricing Models

Cost Factors

Common Use Cases

• Budget planning: Estimate monthly AI costs before deploying Bedrock-powered features in production applications
• Model selection: Compare cost per query across models (Claude Sonnet vs Haiku vs Llama) to find the best price-performance ratio for your use case
• Architecture decisions: Determine whether on-demand, batch, or provisioned throughput is most cost-effective for your usage pattern
• Cost optimization: Identify opportunities to reduce costs through model selection, prompt optimization, or throughput provisioning
• ROI analysis: Calculate the cost of AI-powered features to justify investment against business value generated

Best Practices

1. Start with smaller models — Use Claude Haiku or Llama for tasks that don't require the largest models. Test whether a smaller model meets quality requirements before defaulting to Opus.
2. Optimize prompt length — Shorter, well-structured prompts reduce input token costs. Avoid repeating instructions across requests when using conversation history.
3. Use batch inference for bulk processing — If latency is not critical (analytics, content generation, data processing), batch inference provides up to 50% savings.
4. Monitor token usage — Use AWS Cost Explorer and CloudWatch to track actual token consumption. Unexpected spikes may indicate prompt injection, recursive calls, or inefficient prompts.
5. Evaluate provisioned throughput at scale — Once your usage is predictable and consistent, provisioned throughput can be more cost-effective than on-demand pricing while guaranteeing performance.