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GPUStack

by langgenius · v0.0.15

GPUStack is an open-source GPU cluster manager for running AI models.

28k installsUpdated Jul 16, 2026
Publisher information is incomplete

This community listing does not yet include every recommended support, privacy, pricing, and permission disclosure. Review the available package permissions before installing.

Capabilities

Models

Available inside your emploidai workspace after installation.

Data sources

Available inside your emploidai workspace after installation.

Category

model

Version

0.0.15langgenius

Requirements

Maximum memory 256MB

Pricing

Not disclosed by publisher

Security & access

Review before installing

CompatibleRequires emploidai 1.0.0+

Permissions

  • Uses model capability
  • Uses tool capability

Dependencies

No additional dependencies

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Overview

GPUStack is an open-source GPU cluster manager for running AI models.

Key Features

  • Broad Hardware Compatibility: Run with different brands of GPUs in Apple Macs, Windows PCs, and Linux servers. Broad Model Support: From LLMs to diffusion models, audio, embedding, and reranker models.
  • Scales with Your GPU Inventory: Easily add more GPUs or nodes to scale up your operations.
  • Distributed Inference: Supports both single-node multi-GPU and multi-node inference and serving.
  • Multiple Inference Backends: Supports llama-box (llama.cpp & stable-diffusion.cpp), vox-box and vLLM as the inference backends.
  • Lightweight Python Package: Minimal dependencies and operational overhead.
  • OpenAI-compatible APIs: Serve APIs that are compatible with OpenAI standards.
  • User and API key management: Simplified management of users and API keys.
  • GPU metrics monitoring: Monitor GPU performance and utilization in real-time.
  • Token usage and rate metrics: Track token usage and manage rate limits effectively.

Quickstart

You need setup your own GPUStack server. Please refer to GPUStack official docs quickstart

Configure

After setting up your GPUStack server, you will need the following to configure this plugin:

  • GPUStack Server URL (e.g., http://yourserveraddress:port)
  • GPUStack API Key

Obtain these from your GPUStack server, then enter them into the settings. Click "Save" to activate the plugin.