club-3090
From the repo · “Community recipes for serving LLMs on RTX 3090/4090/5090 CUDA gpus. Multi-engine (vLLM, sglang, llama.cpp and other custom engines) and model-agnostic. Currently shipping Qwen3.8-27B Qwen3.6 35B Gemma 4 26B Gemma 4 31B configs for 1×/2×/4x/8x cards.”
Club-3090 provides community-driven recipes for serving large language models on NVIDIA RTX 3090, 4090, and 5090 CUDA GPUs, supporting multiple engines and models
- •You need to deploy LLMs on a local machine with an RTX 3090, 4090, or 5090 GPU
- •You want to use a specific LLM model like Qwen3.6 or Gemma 4 with a multi-engine setup
- •You require a model-agnostic solution for serving LLMs on your GPU
python run.py --config configs/qwen3.6-27b.json --prompt 'Write a short story about a character who discovers a hidden world'
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/club-3090 && curl -fsSL https://workflowstacks.com/api/skills/club-3090/claude-skill -o ~/.claude/skills/club-3090/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
What's inside — free to inspect
Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/club-3090 && curl -fsSL https://workflowstacks.com/api/skills/club-3090/claude-skill -o ~/.claude/skills/club-3090/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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