LLM Token Cost Calculator

Calculate the cost of your LLM API usage across different models. Get instant pricing estimates and compare costs between providers.

GPT-4

Input: $0.03/1K tokens

Output: $0.06/1K tokens

GPT-3.5 Turbo

Input: $0.0015/1K tokens

Output: $0.002/1K tokens

Claude 2

Input: $0.008/1K tokens

Output: $0.024/1K tokens

PaLM 2

Input: $0.0005/1K tokens

Output: $0.0005/1K tokens

Cost Breakdown

Input Cost: $0.00
Output Cost: $0.00
Monthly Total: $0.00

💡 Cost Saving Tip

Using shorter, more focused prompts can significantly reduce input token costs while maintaining output quality.

About This Calculator

Key Features

  • Real-time Calculations: Instantly see cost updates as you adjust token counts and requests
  • Multi-Model Support: Compare pricing across GPT-4, GPT-3.5, Claude 2, and PaLM 2
  • Separate Token Pricing: Accurate cost breakdown for both input and output tokens
  • Monthly Projections: Calculate costs based on expected monthly usage
  • Interactive Interface: Easy-to-use card selection and input fields
  • Detailed Breakdown: See input costs, output costs, and total expenses

How to Use

  • Select Model: Click on any model card to choose your LLM provider
  • Input Tokens: Enter the number of prompt/input tokens you expect to use
  • Output Tokens: Specify expected completion/output tokens
  • Monthly Requests: Set your expected monthly API call volume
  • View Results: See the cost breakdown update automatically
  • Compare Models: Switch between models to find the most cost-effective option

Perfect For

  • Developers: Plan API costs for applications and estimate usage tiers
  • Product Managers: Compare provider costs and forecast budget requirements
  • Business Analysts: Calculate ROI and prepare cost-benefit analyses
  • Startups: Optimize LLM spending and choose the most cost-effective providers
  • Enterprise Teams: Project scaling costs and plan resource allocation
  • AI Researchers: Compare model costs for research projects and experiments

Cost Optimization Tips

  • Token Efficiency: Write concise prompts to minimize input token costs
  • Model Selection: Use GPT-3.5 for simpler tasks, reserve GPT-4 for complex ones
  • Batch Processing: Combine related requests to reduce API calls
  • Response Length: Set appropriate max_tokens to control output costs
  • Caching: Implement response caching for repeated queries
  • Request Optimization: Use efficient prompt engineering techniques

📝 Pricing Note

Prices shown are based on current public API rates as of March 2024. For the most up-to-date pricing, please refer to each provider's official pricing page. Enterprise pricing may vary based on volume and contract terms.