ModelRefs / Batch Inference — AI Glossary
Batch Inference — AI Glossary
Processing a large volume of model requests offline in bulk, trading latency for cost and throughput efficiency.
Overview
Batch inference jobs run without real-time latency requirements, enabling larger batch sizes and lower GPU idle time. OpenAI Batch API, Anthropic Message Batches, and AWS Bedrock Batch offer ~50% cost reduction vs. real-time. Ideal for embedding generation, classification at scale, and offline eval runs.
Reference details
| Topic | inference |
|---|---|
| Also known as | batch processing, offline inference |
| Last reviewed | 2026-06-24 |
Related terms
Referenced by
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Frequently asked questions
What is Batch Inference?
Processing a large volume of model requests offline in bulk, trading latency for cost and throughput efficiency.
Is Batch Inference the same as batch processing?
Yes — batch processing, offline inference are common aliases for Batch Inference.
What concepts are related to Batch Inference?
Closely related concepts include throughput, inference cost, eval.