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voyage-3-large Cost Calculator - Voyage

Calculate the cost of using voyage-3-large from Voyage for your AI applications

voyage-3-large Cost Calculator

Mode: Embedding

Max: 32,000 tokens

Cost Breakdown

Input Cost$0.00018000
Total Cost$0.00018000

Pricing Details

Input: $0.0000001800 per token
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Model Specifications

Limits

Max Input Tokens32,000
Max Tokens32,000

About voyage-3-large

voyage-3-large is a powerful embedding AI model offered by Voyage. This comprehensive guide provides detailed pricing information, technical specifications, and capabilities to help you understand the costs and features of using voyage-3-large in your embedding applications.

Pricing Information

Input Cost$0.18 per 1M tokens

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

Technical Specifications

Maximum Input Tokens32,000
Maximum Total Tokens32,000

Pro Tip

Use the maximum token limits shown above to understand the model's capacity. This model can handle up to 32,000 input tokens.

When should you use voyage-3-large?

voyage-3-large is best suited for the following scenarios:

  • Semantic search and similarity matching
  • RAG pipelines and vector databases
  • Document clustering and recommendations
When should you avoid voyage-3-large?
  • Complex multi-step reasoning or planning tasks
  • Applications requiring image, audio, or multimodal inputs
  • Very large documents or long conversational histories
  • General-purpose text generation or conversational AI
  • Creative writing or content generation tasks
How does voyage-3-large 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 voyage-3-large pricing
  • voyage-3-large is a embedding and vector search model provided by Voyage.
  • Input tokens are priced at $0.18 per 1M tokens.
  • The model supports a maximum input capacity of 32,000 tokens.
  • Voyage offers voyage-3-large for embedding and vector search workloads — semantic search, similarity matching, recommendation systems, and vector-based applications.

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.