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e5-large-v2 Cost Calculator - OpenRouter

Calculate the cost of using e5-large-v2 from OpenRouter for your AI applications

e5-large-v2 Cost Calculator

Mode: Chat

Max: 512 tokens

Cost Breakdown

Input Cost$0.00001000
Total Cost$0.00001000

Pricing Details

Input: $0.0000000100 per token
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Model Specifications

Limits

Max Input Tokens512
Max Tokens512

About e5-large-v2

e5-large-v2 is a powerful chat AI model offered by OpenRouter. This comprehensive guide provides detailed pricing information, technical specifications, and capabilities to help you understand the costs and features of using e5-large-v2 in your applications.

Pricing Information

Input Cost$0.01 per 1M tokens

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

Technical Specifications

Maximum Input Tokens512
Maximum Total Tokens512

Pro Tip

Use the maximum token limits shown above to understand the model's capacity. This model can handle up to 512 input tokens.

Model Capabilities

Response Schema - Structured output formatting
When should you use e5-large-v2?

e5-large-v2 is best suited for the following scenarios:

  • General-purpose chat and text generation workloads
When should you avoid e5-large-v2?
  • Complex multi-step reasoning or planning tasks
  • Applications requiring image, audio, or multimodal inputs
  • Very large documents or long conversational histories
How does e5-large-v2 compare to similar models?

This model offers competitive input token pricing, making it cost-effective for applications that require extensive context or frequent input processing.

Understanding e5-large-v2 pricing
  • e5-large-v2 is a general-purpose AI model provided by OpenRouter.
  • Input tokens are priced at $0.01 per 1M tokens.
  • The model supports a maximum input capacity of 512 tokens.
  • OpenRouter offers e5-large-v2 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.