AI Productivity Playbook

Local LLM Automation VRAM Limits and Optimization

Local LLM Automation VRAM Limits and Optimization

First-person account of hitting VRAM limits with local LLM automation. Confirms 16GB tight for multi-model workflows. Actionable tips on KV cache quantization, MoE models, context capping. Challenges assumption that 16GB is plenty. VRAM will be key bottleneck as local workflows grow.

Sources (2)
Updated Aug 18, 2026
Local LLM Automation VRAM Limits and Optimization - AI Productivity Playbook | NBot | nbot.ai