llama-3-70b-instruct Cost Calculator - OpenRouter

Calculate the cost of using llama-3-70b-instruct from OpenRouter for your AI applications

llama-3-70b-instruct Cost Calculator

Mode: Chat

Input Tokens

Output Tokens

Cost Breakdown

Input Cost$0.00051000

Output Cost$0.00074000

Total Cost$0.001250

Pricing Details

Input: $0.0000005100 per token

Output: $0.0000007400 per token

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Model Specifications

Limits

Max Tokens8,192

About llama-3-70b-instruct

llama-3-70b-instruct 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 llama-3-70b-instruct in your applications.

Pricing Information

Input Cost$0.51 per 1M tokens

Output Cost$0.74 per 1M tokens

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

When should you use llama-3-70b-instruct?

llama-3-70b-instruct is best suited for the following scenarios:

General-purpose chat and text generation workloads

When should you avoid llama-3-70b-instruct?

Complex multi-step reasoning or planning tasks
Applications requiring image, audio, or multimodal inputs
Very large documents or long conversational histories

How does llama-3-70b-instruct 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 llama-3-70b-instruct pricing

llama-3-70b-instruct is a general-purpose AI model provided by OpenRouter.
Input tokens are priced at $0.51 per 1M tokens.
Output tokens are priced at $0.74 per 1M tokens.
For this model, input tokens are less expensive than output tokens, so optimizing your prompts can help manage costs.
OpenRouter offers llama-3-70b-instruct 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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