Get started with AI inference: Red Hat AI experts explain

Organizations deploying large AI models face rising costs from memory use, latency, and throughput limits. As models scale to billions of parameters, infrastructure demands can become unsustainable without optimization.

This e-book explores efficient AI inference systems, focusing on reducing computational needs while preserving accuracy. Topics include:

· Quantization and sparsity to shrink model size and memory use without performance loss
· Runtime optimizations with vLLM for better throughput and lower latency
· Full-stack strategies combining model compression with serving techniques

Read the e-book to learn how to optimize AI workflows and cut infrastructure costs.