Batch API Savings Calculator for LLM Workloads
Compare the cost of async batch processing against realtime API calls. Enter your request volume and per-call token usage to see how much you save with discounted batch pricing from Anthropic and OpenAI.
0% of realtime spend kept — 0 projected annual savings.
How the LLM batch API savings calculator works
Async batch APIs let you submit large volumes of non-urgent requests that providers process offline and return hours later. Because that traffic is flexible, Anthropic and OpenAI both discount batch completions by roughly 50% versus standard realtime calls. This calculator multiplies your monthly request count by the per-call token cost, applies the discount you select, and reports the difference as both a dollar figure and a percentage.
- Realtime cost = requests × (input tokens × input price + output tokens × output price) ÷ 1,000,000.
- Batch cost = realtime cost × (1 − discount ÷ 100).
- Savings = realtime cost − batch cost, then × 12 for the annual projection.
When batch processing makes sense
Batch is ideal when a human is not waiting on the response. Bulk classification, document summarization, embeddings generation, dataset labeling, and evaluation harnesses all tolerate a 24-hour turnaround in exchange for half the cost. If your workload is interactive, latency-sensitive, or needs streaming, keep it on realtime endpoints.
Tips for maximizing savings
- Coalesce small requests into fewer batch files to stay above the minimum batch size.
- Move evaluation and regression suites entirely to batch — they rarely need realtime results.
- Watch token caps per file: Anthropic caps batch files at 100,000 requests and 256 MB.
- Re-run this calculator whenever pricing changes or volume scales, since savings compound linearly.