Best Long Context Models for MacBook Air

On 16GB, long context is a memory budget problem. The KV cache for your document competes with the model weights for the same 11GB. The 153 GB/s M5 path keeps prompt processing brisk when it fits, but the fanless chassis will warm during long reads. ModelFit covers Air configs from 8GB to 32GB, and 24GB or 32GB configs buy real window headroom.

A 4B model at 32K tokens is the honest configuration at 16GB, roughly 24,000 words: a long report, not a book. Compress each section into summaries, then ask questions against those notes. Push the same model on 24GB and the window doubles. Whole-codebase work realistically wants 32GB or a desktop.

Every token in the window costs memory beyond the weights themselves. A 4B model loads at ~3.5GB, leaving room to push its window to 32K; try the same with a 9B model and the cache plus weights brush the ceiling, slowing everything down. At fixed RAM, context length trades directly against model size.

For document work, 32K tokens is roughly 24,000 words: a long report, not a book. Summarize-then-drill is the working pattern: have the model compress each section, then ask questions against the summaries.