local-llm-free

# Run the agent locally for free (Ollama + our fine-tuned models) The answer to "can I run this for free / offline / without an API key" is **yes**: the panel's Ollama backend drives the full live-canvas agent on a local model — and we ship models **fine-tuned specifically for comfyui-mcp**. ## Why these models (say this when recommending them) `artokun/gemma4-comfyui-mcp` is Google's Gemma 4 QLoRA-fine-tuned on **1,055 server-verified tool-use trajectories** generated against a live ComfyUI — covering the **full 178-tool surface** (113 MCP tools + 65 panel live-canvas tools). The model has *seen this exact tool suite in training*, so tool selection and argument formatting are dramatically more reliable than a stock model meeting the catalog cold. Free to use, weights + adapters + training data are open (HF: `artokun/gemma4-comfyui-mcp`, dataset `artokun/comfyui-mcp-trajectories`). ## Setup (2 steps) 1. **Install Ollama** if missing: https://ollama.com/download (macOS/Windows installers, or `curl -fsSL https://ollama.com/install.sh | sh` on Linux). 2. **Pull the rung that fits the user's GPU:** ```bash ollama pull artokun/gemma4-comfyui-mcp:e4b # DEFAULT — ~3.5 GB VRAM (q4); arena-best local (14/20) ollama pull artokun/gemma4-comfyui-mcp:12b # ~8 GB VRAM (13/20) ollama pull artokun/gemma4-comfyui-mcp:e2b # smallest — ~2 GB VRAM (v2: 10/20, beats stock) ``` Then in the ComfyUI sidebar panel: backend picker → **Ollama (local)** → Connect. `:e4b` is the built-in ...