Teacher With 16GB VRAM Hits a Wall: Local LLMs Keep Failing at MCP Tool Use
whakahere · reddit · 2026-09-03
A primary school teacher building a local AI setup (16GB VRAM workstation, NAS, Tailscale) for admin automation found that even quantized 27B models frequently pick the wrong MCP tools, drift from lesson-plan logic, and ignore skill boundaries — while closed-source models handle the exact same prompts perfectly. He asks the community whether this is a known limitation of small quantized models, how to make tool definitions more robust, and which local models are the gold standard for precise tool calling and multi-step instruction following.
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