Question 1

What is the OpenAI Batch API discount?

Accepted Answer

OpenAI's Batch API offers 50% off standard API prices in exchange for accepting results within 24 hours. For high-volume, latency-tolerant workloads like data enrichment, classification, and content moderation, this cuts costs in half. Batch requests are processed asynchronously in a queue.

Question 2

When should I use batch processing vs real-time AI?

Accepted Answer

Use batch processing when: (1) results aren't needed immediately — nightly reports, weekly enrichment, async analysis; (2) processing large datasets where cost matters more than speed; (3) your workload is predictable and schedulable. Use real-time when users need instant responses (chatbots, live classification).

Question 3

How much can batch processing save at scale?

Accepted Answer

At 1M requests/month with GPT-4o Mini (2K tokens avg), real-time costs ~$1,200/mo. With 50% batch discount: ~$600/mo. At 10M requests, that's a $6,000/month difference — $72,000/year. For compute-heavy models like GPT-4o, savings scale even larger.

Question 4

Are there limits on AI batch job size?

Accepted Answer

OpenAI Batch API has a 50,000 request per batch limit and a 90,000 token per minute queue limit. Results are delivered within 24 hours. Anthropic offers batch processing with similar constraints. For very large volumes, split into multiple batches or use a queue management system.

AI Batch Processing Cost Calculator — Estimate Bulk AI Job Costs

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