Nine coding harnesses vs. your laptop

Local language models on laptops perform poorly in coding harnesses designed for data center APIs due to three main issues: large system prompts and tool schemas that cause long prefill delays (22-226 seconds), reduced context windows after prompt consumption, and excessive side requests that force the model to queue or restart processing. While benchmark speeds like llama-bench suggest feasibility, the actual development experience is sluggish and unreliable because most coding harnesses were built for remote servers, not localhost inference.