developer-roadmap/roadmaps/forward-deployed-engineer/content/inference-optimization@hRTwO-qsk58UpfTKmsTvo.md

Inference Optimization

Inference optimization refers to techniques for making model predictions faster and cheaper without significantly reducing quality. Common approaches include quantization, distillation, response caching, and request batching. Inference costs can become a real issue quickly, and knowing how to optimize without degrading the user experience is a practical skill FDEs should have.

Visit the following resources to learn more:

• @article@Mastering LLM Techniques: Inference Optimization
• @article@How can I optimize for an inference application?
• @video@AI Inference: The Secret to AI's Superpowers