Local Llm Free

Community

artokun

local-llm-free

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.

Overview

Publisher	artokun
Repository	`comfyui-mcp`
Skill name	`local-llm-free`
Stars	811
Forks	137
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by artokun on GitHub. Read the source before you install it.

Installation

Install the Local Llm Free AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/artokun/comfyui-mcp/tree/main/plugin/skills/local-llm-free
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/artokun/comfyui-mcp.git /tmp/comfyui-mcp
mkdir -p .claude/skills
cp -r /tmp/comfyui-mcp/plugin/skills/local-llm-free .claude/skills/local-llm-free

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Local Llm Free in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Local Llm Free on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Local Llm Free is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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)

Install Ollama if missing: https://ollama.com/download (macOS/Windows installers, or curl -fsSL https://ollama.com/install.sh | sh on Linux).
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 else needs configuring once pulled. (Override via the panel's model picker or COMFYUI_MCP_OLLAMA_MODEL.)

Sizing guidance

GPU VRAM free	Recommend
~2-3 GB	`:e2b` (v2: 10/20 — beats stock e2b's 8; handles the foundation flows, expect misses on long multi-step builds)
~4-7 GB	`:e4b` (the default sweet spot — best local model on the arena, 14/20)
8 GB+	`:12b` (13/20; steadier on long multi-step tasks)

Expectations to set

Local models keep tool calling but have limited/no vision. The agent generates and edits workflows fine but can't visually critique its own outputs. Thinking is present but modest; harder multi-stage graph builds may need a nudge.
Audio: these fine-tunes cannot hear. Native Ollama puts audio in the image slot; a namespaced Gemma 4 fork (e.g. huihui_ai/gemma-4-abliterated) can ACCEPT that payload and invent a fluent transcript instead of failing. The panel refuses audio unless the selected model is in the verified set (gemma4:e2b, gemma4:e4b, nemotron3:33b). Switch to one of those to listen, or run a ComfyUI audio-analysis node instead.
First request after connect is slow (cold model load, 30s+). That's normal.
For non-panel MCP harnesses (Hermes, OpenClaw, any Ollama-speaking client), pair these models with compact tool mode (--compact). Full docs: https://comfyui-mcp.artokun.io/docs/local-llms

Sources

Official: https://ollama.com/download and https://comfyui-mcp.artokun.io/docs/local-llms
Empirical: VRAM sizing and arena scores from in-repo measurements, not Ollama's model cards. Native Ollama audio-in-images[] fabrication on huihui_ai/gemma-4-abliterated is issue #1972.

Frequently asked questions

What does the Local Llm Free AI skill do?

Why use Local Llm Free on TypingMind?

Because you install it once and use it with any model. Local Llm Free is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Local Llm Free in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/artokun/comfyui-mcp/tree/main/plugin/skills/local-llm-free. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Local Llm Free?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Local Llm Free?

As many as you like. As long as a model supports skills, you can use Local Llm Free with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Local Llm Free AI skill free?

Yes. It is published on GitHub by artokun under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Discord Clawd

openclaw

OrganizationPopular

Use to talk to the Discord-backed OpenClaw agent/session; not for archive search.

Discord User Post

Post an approved message as the logged-in Discord user through the Discord desktop app. Use for release announcements or other direct user-authored Discord posts; not for OpenClaw channel sends, bots,…

Discrawl

Discord archive: search, sync freshness, DMs, summaries, TUI, repo/release work.

Gitcrawl

GitHub archive: issue/PR search, sync freshness, duplicate clusters, current GitHub handoff, and Gitcrawl repo work.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Run the agent locally for free (Ollama + our fine-tuned models)

Why these models (say this when recommending them)

Setup (2 steps)

Sizing guidance

Expectations to set

Sources

Frequently asked questions

Related AI Skills

Set up your own AI workspace now