# O10: Batchers

- Publisher: NVIDIA Triton Inference Server
- URL: [Primary source](https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/user_guide/batcher.html)
- Published: not stated
- Updated/version date: not established
- Accessed: 2026-10-22
- Type: official server documentation
- Verification: opened source, rather than relying on a search excerpt

## Supported finding

Dynamic batching groups requests for throughput and exposes queue-delay limits. Tuning should observe a latency budget.

## Limits and transfer

Documented dynamic batcher targets stateless models. LLM runtimes may use distinct continuous-batching mechanisms.

## Use in the session

Mechanism and decision conditions. Retain the qualifications when translating the finding into slide copy. No source establishes Knauf's savings.