twelvelabs.marengo-embed-2-7-v1:0 Cost Calculator - AWS Bedrock

Calculate the cost of using twelvelabs.marengo-embed-2-7-v1:0 from AWS Bedrock for your AI applications

twelvelabs.marengo-embed-2-7-v1:0 Cost Calculator

Mode: Embedding

Input Tokens

Max: 77 tokens

Cost Breakdown

Input Cost$0.070000

Total Cost$0.070000

Pricing Details

Input: $0.00007000 per token

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Model Specifications

Limits

Max Input Tokens77

Max Tokens77

About twelvelabs.marengo-embed-2-7-v1:0

twelvelabs.marengo-embed-2-7-v1:0 is a powerful embedding AI model offered by AWS Bedrock. This comprehensive guide provides detailed pricing information, technical specifications, and capabilities to help you understand the costs and features of using twelvelabs.marengo-embed-2-7-v1:0 in your embedding applications.

Pricing Information

Input Cost$70.00 per 1M tokens

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

Technical Specifications

Maximum Input Tokens77

Maximum Total Tokens77

Pro Tip

Use the maximum token limits shown above to understand the model's capacity. This model can handle up to 77 input tokens.

When should you use twelvelabs.marengo-embed-2-7-v1:0?

twelvelabs.marengo-embed-2-7-v1:0 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 twelvelabs.marengo-embed-2-7-v1:0?

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 twelvelabs.marengo-embed-2-7-v1:0 compare to similar models?

This model sits in the middle of its category in terms of pricing and capabilities, making it a balanced option for general workloads.

Understanding twelvelabs.marengo-embed-2-7-v1:0 pricing

twelvelabs.marengo-embed-2-7-v1:0 is a embedding and vector search model provided by AWS Bedrock.
Input tokens are priced at $70.00 per 1M tokens.
The model supports a maximum input capacity of 77 tokens.
AWS Bedrock offers twelvelabs.marengo-embed-2-7-v1:0 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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