local-llm-free

Featured

Run the ComfyUI agent locally for FREE with no subscription, no API key, and fully offline, using our gemma4 models fine-tuned on the comfyui-mcp tool suite via Ollama. Use when the user asks about running locally, running for free, offline use, avoiding API costs, Ollama setup, or which local model to pick.

AI & Automation 738 stars 120 forks Updated yesterday MIT

Install

View on GitHub

Quality Score: 88/100

Stars 20%
96
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# 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 **all 178 tools** (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 far 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 default, so nothing els...

Details

Author
artokun
Repository
artokun/comfyui-mcp
Created
6 months ago
Last Updated
yesterday
Language
TypeScript
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category

AI & Automation Listed

local-llm-agent

Use the high-end LOCAL LLMs on this machine as a real agent/coding substrate (not just Claude). Dual RTX 5090 (64GB VRAM) + ollama already installed and serving. Best agentic-coding local model: qwen3-coder:30b. Covers how to pull, run, call (CLI / HTTP / OpenAI-compatible / function-calling), route through the AIOS provider harness, and use as a heterogeneous arm in absorption-probe. Per feedback_use_all_substrates_not_own_head — don't solve from one model.

0 Updated 3 weeks ago
cjw0076
AI & Automation Listed

local-offload-setup

Use when setting up the "local-offload" harness on a Windows machine — a free local Gemma-4 cascade that lets a coding agent delegate short-context grunt work (summarize / classify / extract / triage) so those tokens never hit the cloud context. Cross-vendor: NVIDIA (CUDA, ≥8GB), AMD Radeon incl. RDNA3 iGPUs like the 780M/gfx1103 (Vulkan, native Windows), or CPU-only fallback. Builds a pinned llama.cpp + llama-swap stack, pulls the Gemma-4 QAT family (E2B/E4B/26B-A4B) + EmbeddingGemma, builds the Go CLI/MCP + local coding agent, and registers it with Claude Code. Triggers: "set up local offload", "install the local-offload harness", "offload model setup", "give Claude a free local model", "install the AMD/NVIDIA offload stack".

2 Updated today
dmmdea
AI & Automation Featured

ai-local-model-ops

Runs local and self-hosted LLM workflows with Ollama, LM Studio, MLX, Open WebUI, llamafile, and adapters. Use when operating private model stacks.

87 Updated 1 weeks ago
vasilyu1983