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Llama-3.3-70B-Instruct Cost Calculator - Nscale

Calculate the cost of using Llama-3.3-70B-Instruct from Nscale for your AI applications

Llama-3.3-70B-Instruct Cost Calculator

Mode: Chat

Cost Breakdown

Input Cost$0.00020000
Output Cost$0.00020000
Total Cost$0.00040000

Pricing Details

Input: $0.0000002000 per token
Output: $0.0000002000 per token
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About Llama-3.3-70B-Instruct

Llama-3.3-70B-Instruct is a powerful chat AI model offered by Nscale. This comprehensive guide provides detailed pricing information, technical specifications, and capabilities to help you understand the costs and features of using Llama-3.3-70B-Instruct in your applications.

Pricing Information

Input Cost$0.20 per 1M tokens
Output Cost$0.20 per 1M tokens

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

When should you use Llama-3.3-70B-Instruct?

Llama-3.3-70B-Instruct is best suited for the following scenarios:

  • General-purpose chat and text generation workloads
When should you avoid Llama-3.3-70B-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-3.3-70B-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-3.3-70B-Instruct pricing
  • Llama-3.3-70B-Instruct is a general-purpose AI model provided by Nscale.
  • Input tokens are priced at $0.20 per 1M tokens.
  • Output tokens are priced at $0.20 per 1M tokens.
  • For this model, input tokens are more expensive than output tokens, so optimizing your prompts can help manage costs.
  • Nscale offers Llama-3.3-70B-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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