Calculate and compare the cost of using large language model APIs. Enter your token usage, request volume, and caching preferences to estimate daily, monthly, and annual spend across major providers.
Cost per Request
$0.006000
Daily Cost
$0.60
Monthly Cost
$18.00
Annual Cost
$219.00
Requests per $1
166
Monthly cost for same usage across each provider's top model
Input vs output token costs per request
| Model | Input/1M | Output/1M | Context | Monthly |
|---|---|---|---|---|
| GPT-4.1selected | $2.00 | $8.00 | 1M | $18.00 |
| GPT-4o | $2.50 | $10.00 | 128K | $22.50 |
| o3 | $2.00 | $8.00 | 200K | $18.00 |
| o4-mini | $0.55 | $2.20 | 200K | $4.95 |
| GPT-4.1-mini | $0.40 | $1.60 | 1M | $3.60 |
| GPT-4.1-nano | $0.10 | $0.40 | 1M | $0.90 |
LLM API costs are based on token usage — the number of input tokens (your prompts) and output tokens (model responses) per request. Prices vary significantly across providers and models, with larger models costing more per token but often producing higher quality results. Caching and batch processing can substantially reduce costs for high-volume applications.
Pricing data is approximate and may not reflect the latest changes. Always verify current rates on provider pricing pages before making purchasing decisions.
Input tokens are the text you send to the API (your prompt), while output tokens are the text the model generates in response. Pricing differs for each direction — output tokens are typically 3-5x more expensive than input tokens.
Prompt caching stores frequently used prompt prefixes so you don't pay full price to resend them. Cached input tokens cost 50-90% less than regular input tokens, making it ideal for applications with repeated system prompts or context.
The Batch API is ideal for non-time-sensitive workloads like data processing, content generation, or evaluation tasks. It typically offers a 50% discount in exchange for longer processing times (up to 24 hours).
A rough rule of thumb is that 1 token is approximately 4 characters or 0.75 words in English. A 500-word prompt is roughly 670 tokens. Most API providers offer tokenizer tools to get exact counts.
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