In our series on Docker Model Runner, we've explored Docker Model Runner's role in simplifying local AI development and its strategic use of OCI artifacts for model management. Now, we peel back another layer to examine a critical aspect for any engineer working with Large Language Models (LLMs): performance. How does Docker Model Runner achieve the responsiveness needed for an efficient local development loop? The answers lie in its architectural choices, particularly its embrace of host-nat...
