LLM & OpenAI API Pricing Calculator

Estimate & Compare LLM APIs Cost 

Streamlined Pricing for
OpenAI API Services

OpenAI, Anthropic, Google, Cohere, and Meta offer various AI models for specific tasks. Knowing how they price these models is essential for businesses and developers. Check the suitable models from below along with their pricing and make informed decisions for your projects.

Understanding OpenAI API Pricing

1. Tokens and Context Length Simplified

OpenAI API pricing primarily hinges on: tokens and context length. Tokens, generally three-quarters of a word, form the cost basis, as reflected in the OpenAI token calculator. Longer context lengths enable more complex tasks but increase the OpenAI API cost. This concept directly influences GPT API pricing, including chat GPT API pricing. The blend of token count and context length majorly determines the overall OpenAI API pricing.

2. Model Choice and Usage

LLM APIs pricing is based on model choice and usage.

• OpenAI GPT-4: A leading-edge model, GPT-4 boasts extensive general knowledge and specialized expertise. Ideal for complex instructions and problem-solving, it offers precise outputs but at a higher cost. GPT-4 Turbo, it’s faster and more affordable variant, supports a substantial 128K context limit, enhancing its range of applications.
• OpenAI GPT-3.5 Turbo: Optimized for dialogue and conversational interfaces, GPT-3.5 Turbo is the go-to model for chatbot technology. It stands out for its speed and cost-effectiveness in text generation, making it a popular choice for real-time, interactive applications.
• Anthropic Claude 2: Known for its impressive 100K context length, Claude 2 excels in summarizing large documents and handling detailed Q&A sessions. While its extensive context capacity is a significant advantage, it comes at the cost of speed and affordability.
• Llama 2: Developed by Meta, this open-source model is akin to GPT-3.5 Turbo in performance. Notably cost-effective, it specializes in English text summarization and question answering. Although it’s limited to English, its affordability and versatility make it a strong contender in the AI landscape.
• Gemini Series by Google: This series includes Gemini Ultra, Pro, and Nano. Gemini Ultra rivals OpenAI’s GPT-4 in capabilities, while Gemini Pro aligns more with GPT-3.5 in performance. This range offers versatile, multimodal functionalities, catering to diverse AI needs.
• PaLM 2 by Google: PaLM 2 is distinguished by its advanced multilingual capabilities and reasoning prowess. Trained on a vast, diverse dataset, it excels in tasks requiring complex language understanding and translation, including coding, making it ideal for academic and technical applications.
• Mistral AI Models: Mistral AI offers accessible, open-source models like Mistral 7B and Mixtral, which provide rapid and cost-efficient solutions. These models compete with larger models like GPT-3.5 Turbo in performance, offering a viable alternative for budget-conscious AI applications.

Use the OpenAI token calculator for precise GPT API pricing.