Compare OpenAI & Top LLM API Pricing Instantly

Text generation API costs are calculated based on token usage - the fundamental unit of text processing. Providers charge for:

• Input tokens: Text sent to the model (prompts, instructions, context)
• Output tokens: Text generated by the model (completions, responses)

Each provider (OpenAI, Anthropic, Google Gemini, etc.) sets unique pricing tiers per 1,000,000 tokens, with premium models typically costing more than base models.

Input tokens represent the text you send to the LLM API (your prompt or context), while output tokens are what the model generates in response. For example:

• Input: "Write a summary about Paris." (6 tokens)
• Output: "Paris is the capital of France and a global center for art, fashion, and culture." (18 tokens)

Most providers charge different rates for input versus output tokens, with output tokens typically costing 2-5x more than input tokens.

Our Text generation API pricing database is monitored and updated regularly. We track official pricing pages, API documentation, and company announcements to try to ensure accuracy across all models from OpenAI, Anthropic, Google, Mistral, Cohere, and DeepSeek. If you notice any discrepancies, please feel free to send us a message to test@test.de.

The most cost-effective LLM depends on your specific requirements. OpenAI's GPT-4o-mini offers competitive pricing for general applications, while Anthropic's models excel at processing lengthy documents. Mistral and DeepSeek provide affordable alternatives for certain tasks. Our comparison tool helps you calculate exact costs based on your expected token usage and performance needs.

Yes, several strategies can optimize API costs:

• Prompt engineering: Craft concise, effective prompts to reduce input tokens
• Response parameters: Set maximum token limits for outputs
• Caching: Store common responses to avoid redundant API calls
• Model selection: Choose the most affordable model that meets your quality requirements
• Batch processing: Combine multiple requests where possible

Each LLM has a maximum context window (the total tokens it can process at once). Context window sizes vary dramatically across providers, from Google Gemini's expansive 2M token capacity to more modest windows in other models. While OpenAI's GPT-4o and GPT-4o-mini share the same context window size, the mini version offers a more economical option. Similarly, Claude models offer large windows at different price points. Our calculator helps you determine if using a larger context model is more economical than breaking your task into multiple calls with a smaller-context, less expensive model.

While we strive to maintain accurate pricing information across all LLM providers, the rapid evolution of AI services means occasional discrepancies may occur. If you spot any errors in our pricing data or calculations, please feel free to contact us at test@test.de. We appreciate user feedback as it helps us maintain the most reliable comparison tool possible. However, we recommend that all users conduct their own due diligence and verify current pricing with the official provider documentation before making final decisions for production systems or budget-critical applications.