Run LLMs Locally with awesome-local-llm
Awesome-local-llm provides a curated list of resources and tools to help founders self-host and run large language models (LLMs) locally.
- •When you need to deploy AI models on-premises due to data privacy concerns
- •When you want to reduce cloud costs by running AI workloads locally
- •When you need more control over the AI infrastructure and model updates
To get started with a specific LLM platform, for example, Docker, paste the command `docker run -it --rm rafsk/llm-local` to run a local LLM instance
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/awesome-local-llm && curl -fsSL https://workflowstacks.com/api/skills/awesome-local-llm/claude-skill -o ~/.claude/skills/awesome-local-llm/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Run LLMs Locally with awesome-local-llm is a documents-only repository (2 doc files) — something you read, not something you run. There is nothing to install. Last commit a month ago, MIT license.
- 1README.mdStart here — what it does and how to install it
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
A prompt/skill package — nothing to install beyond adding it to your AI tool.
mkdir -p ~/.claude/skills/awesome-local-llm && curl -fsSL https://workflowstacks.com/api/skills/awesome-local-llm/claude-skill -o ~/.claude/skills/awesome-local-llm/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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