Batch API Savings — When It's Worth It
Real batch API savings calculations across different workload sizes and providers.
Assumptions
- Standard: $3/M input, $15/M output
- Batch: ~50% off standard = $1.50/M input, $7.50/M output
- Workloads: document processing, overnight analytics, content moderation, dataset annotation
Base model: Claude Sonnet 5 — $3/M input · $15/M output · 2026-08-19
Cost breakdown by component
How to cut this cost by 50%+
These are estimates based on typical patterns. Enter your specific token counts and volume for a precise calculation.
Frequently Asked Questions
Which workloads qualify for batch API?
Any non-real-time processing: content moderation queues, document classification, data extraction pipelines, overnight analytics, eval runs, dataset annotation. The constraint is results within 24 hours (OpenAI) or 24 hours (Anthropic). Real-time user-facing features don't qualify.
Is batch API worth using at low volume?
Yes — even at 10k requests/month, batch saves 50%. At $3/M input standard and 1,000 tokens average: 10M tokens/month = $30 standard vs $15 batch. $15/month saved. Still worth it for any async workload with no additional implementation effort.
Pricing verified 2026-08-20. All figures are estimates with stated assumptions. See methodology.