ai-agent

gpustack: High-Performance AI Serving

Get on-demand GPU instances for AI model deployment with gpustack, ideal.
intermediate1-2 hours💵 Free + LLM API costs
5,419 stars601 forksPythonGuide quality 8/10Updated 7/31/2026100% free · open source
What it is

Manage a group of computers with good graphics cards to work together on AI tasks.

Real use case example

"A founder wants to build a high-quality chatbot for their e-commerce website. They create a virtual cluster using GpuStack, connect it to their preferred AI model, and start processing customers' queries in real-time. The founder can easily scale their cluster up or down as needed to handle changing traffic."

Best insideClaude DesktopCursor
When to use it
  • When deploying large-scale AI models that require significant GPU resources
  • When needing to orchestrate multiple AI models and inference engines
  • When requiring a scalable and configurable GPU cluster for AI workloads
Ready-to-paste prompt
gpustack deploy --model resnet50 --engine vLLM --gpu-type NVIDIA_A100 --num-gpus 4
Heads up: Ensure you have a compatible NVIDIA GPU driver installed and configured on your system, as gpustack requires this to function correctly
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

✅ Light setup

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/gpustack && curl -fsSL https://workflowstacks.com/api/skills/gpustack/claude-skill -o ~/.claude/skills/gpustack/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

Quick Actions
Details
Creator
gpustack
Language
Python
Category
ai-agent
Published
5/11/2024

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