Inference Optimization

Definitions

1. The process of making model inference faster, cheaper, or more efficient through techniques such as quantization, batching, caching, compilation, or smarter routing. Inference optimization is often necessary before AI features can scale economically.

   In plain English: Improving how efficiently an AI model runs at inference time.

   Example: "Most of the serving win came from inference optimization at the runtime level rather than any change to the base model."

Related Terms

• Floating Point Quantization
• INT4
• INT8
• AI Efficiency
• AI Optimization
• AI Tuning
• Implicit Reasoning
• Inference Budget
• Inference Time
• Neural Network Pruning
• Objective Function
• Reward Engineering
• Score Function
• Training Dynamics