How much do tokens cost? LLM pricing per million tokens compared across providers
LLM API pricing is quoted per million tokens, split between input tokens (what you send) and output tokens (what the model generates). Output tokens typically cost 3-5x more than input tokens because generation is computationally more expensive. The cheapest models (DeepSeek V4 Flash, GPT-5.4 Nano) cost under $0.50 per million input tokens. The most expensive (Claude Opus 4.7) costs $15 per million input tokens.
How this is calculated
To calculate cost: (input_tokens / 1,000,000) × input_price + (output_tokens / 1,000,000) × output_price. A single ChatGPT interaction with a 500-token prompt and 200-token response on GPT-5.4 costs roughly $0.003. A high-volume application processing 1 million requests per day with 1,000 input tokens and 500 output tokens each on GPT-5.4 costs about $7,500 per day. Prompt caching dramatically reduces costs for repeated content: cached input tokens on GPT-5.4 cost $0.62 per million (75% discount). Batch mode (24-hour turnaround) gives a 50% discount. Always check if your use case qualifies for caching or batch pricing before scaling.
Verdict
Token costs are small per-request but add up fast at scale. Use prompt caching for repeated content, batch mode for non-urgent processing, and cheaper models for tasks that don't need frontier intelligence. The built-in LLM Pricing Calculator on this site estimates costs across models and usage patterns.
More Tokens scenarios
Related guides
Frequently asked questions
What is a token in an LLM?
How accurate is this token counter?
Why do different models report different token counts?
Is my text sent to a server?
Related tools
LLM API Pricing Calculator
Compare API costs across major models (OpenAI, Anthropic, Google) with prompt caching.
Use tool ➜LLM VRAM Calculator
Calculate the VRAM needed to run or fine-tune any LLM at any quantization.
Use tool ➜JSON Formatter
Validate, format, and minify JSON data with syntax highlighting.
Use tool ➜