ai-agent

gpustack: Scale AI Model Serving on GPU Clusters with Ease

Deploy high‑performance LLM inference (vLLM, SGLang) on on‑demand GPU instances and get SSH access for rapid iteration. Ideal for founders building AI‑powered products. 5.8k+ GitHub stars

From the repo · “A GPU cluster manager for high-performance AI model serving (vLLM, SGLang) and on-demand SSH-accessible GPU instances.”

intermediate⏱ 1-2 hours💵 Free + LLM API costs
5,879 stars+41★ this week695 forksPythonGuide quality 8/10 · reviewed Oct 6Updated 10/23/2026100% 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

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✅ 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

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

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How gpustack: Scale AI Model Serving on GPU Clusters with Ease works
Codeflow
Free to inspect

Gpustack: Scale AI Model Serving on GPU Clusters with Ease is a very large Python project (~148k lines across 440 code files, plus 212 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, Apache-2.0 license, has a test suite.

Size
Very large codebase
~148k lines · 440 code files · days to read — use, don't read
Setup
One-command install
Installs like a normal app. Reading the code is optional.
Runs on
Python
No API keys detected
Python 98%Shell 1%Jinja 1%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    gpustack/main.py
    Where the program starts running
  4. 4
    pyproject.toml
    Dependencies and the commands it exposes
  5. 5
    gpustack/__init__.py
    Inside gpustack/ — the main logic begins here
What's in each folder
gpustack/Core code — the actual logic412 files
docs/Documentation400 files
pack/Folder112 files
hack/Helper scripts36 files
charts/Folder21 files
docker-compose/Folder10 files
tests/Tests — proof it works300 files
static/Images & static assets47 files
READMEHas testsDocumentedCI checksApache-2.0 licenseUpdated this month
Quick Actions
Details
Creator
gpustack
Language
Python
Category
ai-agent
Published
5/11/2024

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