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bge-m3 Cost Calculator - Novita

Calculate the cost of using bge-m3 from Novita for your AI applications

bge-m3 Cost Calculator

Mode: Embedding

Max: 8,192 tokens

Cost Breakdown

Input Cost$0.00001000
Total Cost$0.00001000

Pricing Details

Input: $0.0000000100 per token
Output: $0.0000000100 per token
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Model Specifications

Limits

Max Input Tokens8,192
Max Output Tokens96,000
Max Tokens96,000

About bge-m3

bge-m3 is a powerful embedding AI model offered by Novita. This comprehensive guide provides detailed pricing information, technical specifications, and capabilities to help you understand the costs and features of using bge-m3 in your embedding applications.

Pricing Information

Input Cost$0.01 per 1M tokens
Output Cost$0.01 per 1M tokens

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

Technical Specifications

Maximum Input Tokens8,192
Maximum Output Tokens96,000
Maximum Total Tokens96,000

Pro Tip

Use the maximum token limits shown above to understand the model's capacity. This model can handle up to 8,192 input tokens. The maximum output length is 96,000 tokens.

When should you use bge-m3?

bge-m3 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 bge-m3?
  • 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 bge-m3 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 bge-m3 pricing
  • bge-m3 is a embedding and vector search model provided by Novita.
  • Input tokens are priced at $0.01 per 1M tokens.
  • Output tokens are priced at $0.01 per 1M tokens.
  • The model supports a maximum input capacity of 8,192 tokens.
  • Maximum output length is 96,000 tokens.
  • For this model, input tokens are more expensive than output tokens, so optimizing your prompts can help manage costs.
  • Novita offers bge-m3 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.

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