LLM Inference Cost Calculator
Estimate the daily and monthly cost of running an LLM workload in production — across providers, with prompt caching and multi-model comparison.
Inputs
Input: $5.00/1M tokens · Output: $20.00/1M tokens · Cached: $1.25/1M
Average tokens in each prompt/context sent to the model
Average tokens in each model response
Total API calls your application makes daily
Used to compute cost per user
0%45%90%
Percentage of input tokens served from prompt cache (reduces input cost).
Configure your workload and click Calculate to estimate production costs.
Cost Reduction Tips
- • Prompt caching is the single biggest lever — even 30% cache hit rate cuts input costs significantly.
- • Use a smaller model for classification, routing, and simple generation steps.
- • Trim system prompts aggressively — every 100 tokens saved × daily requests × 30 days adds up fast.
- • Streaming does not reduce cost, but it improves perceived latency for end users.
- • For agent workflows, multiply this estimate by your average number of LLM calls per task.