# DualCoder/vgpu_unlock

Unlock vGPU functionality for consumer grade GPUs.

Repository: https://github.com/DualCoder/vgpu_unlock
Canonical: https://ross.abutalabs.com/products/vgpu_unlock
Language: C
License: MIT
License Family: permissive
Last push: 2023-02-28T18:32:51+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2043, "days_push": 1282, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5300, forks 470 (observed 2026-08-28T04:09:15.294713+00:00)

## What it is
A Linux tool that patches the NVIDIA GRID vGPU driver to unlock vGPU functionality on consumer-grade GeForce and Quadro GPUs. It works by hooking the vGPU daemon and kernel module via Frida and a linker script to bypass NVIDIA's software restriction to datacenter cards.

## Use cases
- enable vgpu on a consumer geforce gpu
- share one gpu across multiple vms
- set up gpu virtualization for a home lab
- run vgpu on pascal or turing cards
- give cloud gaming vms gpu acceleration

## When to choose
- you want NVIDIA vGPU on a consumer Maxwell-to-Turing GPU on Linux
- you need to split one GPU among several VMs
- you already have access to the NVIDIA GRID vGPU driver

## When to avoid
- you only have an Ampere or newer GPU (support incomplete)
- you cannot obtain the NVIDIA GRID vGPU driver
- you need a guaranteed, officially supported solution
- you run Windows or macOS hosts

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: security, developer-tools, graphics
- domain: hardware, self-hosted
- platform: python, cli
- tags: vgpu, nvidia, gpu-virtualization, gpu-passthrough, frida, kernel-module, home-lab, virtualization, linux

## Member repositories
- DualCoder/vgpu_unlock (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:15.294713+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:59:08.722400+00:00, confidence not recorded.
  - readme: https://github.com/DualCoder/vgpu_unlock (fetched 2026-08-28T04:09:15.294713+00:00, sha d3cde40d8553)
- Data as of 2026-08-30T08:39:29.467469+00:00.