Local LLM developers eye smaller models, massive unified memory

The era of relying entirely on massive cloud-based models is ending as local inference becomes incredibly capable and accessible. Small models (1B-7B) are achieving performance parity with much larger models through quantization and knowledge distillation. Apple's unified memory architecture is positioned to dominate local inference by eliminating VRAM bottlenecks for huge models. The tooling ecosystem has matured from complex setups to one-click deployments via platforms like Ollama and LM Studio.