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us.anthropic.claude-3-7-sonnet-20250219-v1:0 Cost Calculator - Bedrock Converse

Calculate the cost of using us.anthropic.claude-3-7-sonnet-20250219-v1:0 from Bedrock Converse for your AI applications

us.anthropic.claude-3-7-sonnet-20250219-v1:0 Cost Calculator

Mode: Chat

Max: 200,000 tokens

Max: 8,192 tokens

Cost Breakdown

Input Cost$0.003000
Output Cost$0.015000
Total Cost$0.018000

Pricing Details

Input: $0.00000300 per token
Output: $0.00001500 per token
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Model Specifications

Capabilities

✓Function Calling
✓Vision
✓Reasoning

Limits

Max Input Tokens200,000
Max Output Tokens8,192
Max Tokens8,192

About us.anthropic.claude-3-7-sonnet-20250219-v1:0

us.anthropic.claude-3-7-sonnet-20250219-v1:0 is a powerful chat AI model offered by Bedrock Converse. This comprehensive guide provides detailed pricing information, technical specifications, and capabilities to help you understand the costs and features of using us.anthropic.claude-3-7-sonnet-20250219-v1:0 in your applications.

Pricing Information

Input Cost$3.00 per 1M tokens
Output Cost$15.00 per 1M tokens

Note: Use the interactive calculator above to estimate costs for your specific usage patterns.

Technical Specifications

Maximum Input Tokens200,000
Maximum Output Tokens8,192
Maximum Total Tokens8,192

Pro Tip

Use the maximum token limits shown above to understand the model's capacity. This model can handle up to 200,000 input tokens. The maximum output length is 8,192 tokens.

Model Capabilities

✓Function Calling - Execute custom functions and tools
✓Vision - Process and understand images
✓Advanced Reasoning - Complex problem-solving capabilities
✓Prompt Caching - Optimize repeated prompts
✓Response Schema - Structured output formatting
When should you use us.anthropic.claude-3-7-sonnet-20250219-v1:0?

us.anthropic.claude-3-7-sonnet-20250219-v1:0 is best suited for the following scenarios:

  • Long-context chat and document analysis
  • Agent workflows with large memory windows
  • Agentic systems with function or tool calling
  • Workflow automation and API orchestration
  • Multimodal applications requiring image or audio processing
  • Content analysis across multiple media types
  • Complex problem-solving and multi-step reasoning tasks
  • Planning and strategic decision-making applications
When should you avoid us.anthropic.claude-3-7-sonnet-20250219-v1:0?
  • High-volume text generation where output cost dominates
  • Streaming or verbose response workloads
How does us.anthropic.claude-3-7-sonnet-20250219-v1:0 compare to similar models?

This model supports a larger context window than many alternatives, making it suitable for long-form inputs and memory-intensive applications.

Understanding us.anthropic.claude-3-7-sonnet-20250219-v1:0 pricing
  • us.anthropic.claude-3-7-sonnet-20250219-v1:0 is a general-purpose AI model provided by Bedrock Converse.
  • Input tokens are priced at $3.00 per 1M tokens.
  • Output tokens are priced at $15.00 per 1M tokens.
  • The model supports a maximum input capacity of 200,000 tokens.
  • Maximum output length is 8,192 tokens.
  • For this model, input tokens are less expensive than output tokens, so optimizing your prompts can help manage costs.
  • The model includes vision capabilities for processing and analysing images.
  • Supports function calling for executing custom functions and tools.
  • Features advanced reasoning capabilities for complex problem-solving tasks.
  • Features prompt caching to optimize costs for repeated prompts.
  • Bedrock Converse offers us.anthropic.claude-3-7-sonnet-20250219-v1:0 for general-purpose AI workloads — general-purpose AI workloads.

How to Use This Calculator

Step 1: Enter the number of input tokens you expect to use. Input tokens include your prompt, system messages, and any context you provide to the model.

Step 2: Specify the number of output tokens you anticipate. Output tokens are the text generated by the model in response to your input.

Step 3: Review the cost breakdown to see the total estimated cost for your usage. The calculator automatically updates as you adjust the token counts.

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