Which OpenAI model is most cost-effective?

GPT-3.5 Turbo is the most cost-effective for simple tasks at $0.50/M input tokens. GPT-4o offers the best price-performance balance at $2.50/M for most applications. GPT-4 is best for complex reasoning but costs 12x more than GPT-3.5 Turbo. Use the simplest model that meets your quality needs.

How can I reduce OpenAI API costs?

Reduce prompt length (fewer input tokens). Implement semantic caching for repeated queries. Use GPT-3.5 Turbo for simple tasks and GPT-4o only when needed. Set max_tokens limits. Process in batches (50% discount). Use streaming for better user experience without cost difference.

Does OpenAI offer volume discounts?

Yes, OpenAI offers committed throughput tiers with discounted pricing for high-volume users ($10K+/month). They also have an API credits program for startups through Microsoft for Startups. Batch API calls offer 50% discount for non-real-time processing.

What is token caching and how does it save money?

OpenAI and other providers offer automated prompt caching - frequently used prompt prefixes are cached and charged at a lower rate (approximately 50% discount on cached input tokens). This significantly reduces costs for applications with consistent system prompts or few-shot examples.

How do fine-tuned models compare in cost?

Fine-tuned GPT-3.5 Turbo costs $3.00/M input tokens and $6.00/M output tokens - 6x and 4x the base model. However, fine-tuned models often need shorter prompts (no few-shot examples needed), reducing total tokens per call by 30-50%. Evaluate total cost, not per-token price.

What is the difference between prompt tokens and completion tokens?

Prompt tokens are the input you send to the API (system message, user message, conversation history). Completion tokens are the model's response. Most applications use 2-3x more input than output tokens. Both are billed, typically at different rates.

How do I estimate tokens before making an API call?

Use OpenAI's tiktoken library to count tokens client-side before sending. Rule of thumb: 1 token ≈ 0.75 words in English, 1 token ≈ 0.5 words in code. Most prompts are 500-2000 tokens. Responses for chat average 200-800 tokens.

Are there open-source alternatives to reduce costs?

Yes. Llama 3 (Meta), Mistral, and DeepSeek models can be self-hosted or accessed through providers like Together AI, Groq, and Perplexity at lower costs. Self-hosting has high fixed infrastructure costs but near-zero per-token costs at scale - break-even is typically 5-10M tokens/day.

ChatGPT API費用計算機

モデル（GPT-4o、GPT-4、GPT-3.5 Turbo）、トークン数、使用量に応じたOpenAI ChatGPT API費用を計算します。