Question 1

What is batch processing in AI APIs?

Accepted Answer

Batch processing submits multiple requests together for asynchronous processing. OpenAI Batch API offers 50% discount vs synchronous calls. Processing takes 24-48 hours. Ideal for non-urgent bulk workloads: document analysis, content generation, data extraction.

Question 2

How much cheaper is batch processing?

Accepted Answer

OpenAI Batch API: 50% discount on standard pricing. Claude: no official batch discount. Gemini: batch mode available with regional discounts. Savings offset by 24-48 hour latency. Best for workloads tolerating delay.

Question 3

When should I use batch vs synchronous API?

Accepted Answer

Use batch when: deadline >24 hours, processing >1000 documents, cost sensitivity high, no user waiting. Use synchronous when: real-time response needed, interactive workflows, urgent processing, debugging/testing phase.

Question 4

What are batch API rate limits?

Accepted Answer

OpenAI Batch: submit up to 100,000 requests per batch file, 500 batch jobs active. Claude: no batch endpoint. Gemini: varies by quota. Batch limits are higher than synchronous but processing time adds delay budget.

Question 5

How do I structure batch API requests?

Accepted Answer

Structure as JSONL file: each line is {custom_id, method, url, body}. Upload file, create batch job, wait 24-48 hours, retrieve results file. Parse results by custom_id matching. Handle partial failures per-request.

AI Batch Processing Cost Calculator

AI Batch Processing Cost Calculator

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