Taming AI costs: Leaner models for smarter agentic use

This post details strategies for reducing AI costs in agentic systems by leveraging leaner models. It discusses techniques such as model distillation, quantization, and efficient inference techniques to achieve comparable performance to larger models with lower computational overhead. The post emphasizes the trade-offs between model size, performance, and cost, providing insights into selecting and optimizing models for specific agentic tasks to minimize Total Cost of Ownership (TCO).