Open source gpu projects
Every project in the registry tagged gpu, ranked by real GitHub adoption.
High-performance terminal with GPU acceleration
📊 A simple command-line utility for querying and monitoring GPU status
High-performance inference framework for large language models, focusing on efficiency, flexibility, and availability.
OpenLake is a high performance storage engine for efficient LLM inference and GPU Training
GPU orchestration across clouds, Kubernetes, and on-prem
Open Source Continuous Inference Benchmark Research Platform — Kimi K3 2.8T, MiniMax M3, DeepSeekv4, GLM5 - GB200 NVL72 vs MI355X vs B200 vs GB300 NVL72 & soon™
Serverless GPU compute with sub-second cold starts
🔥 Real-time NVIDIA GPU dashboard
Pure Rust + CUDA LLM inference engine — no PyTorch, OpenAI-compatible, serves Qwen3 to Kimi-K2
High-performance serverless GPU task orchestration — the scheduling layer behind wavespeed.ai
Related tags
Frequently asked questions
How many open source gpu projects are there?
This registry tracks 10 projects tagged gpu, with 85,253 GitHub stars between them. The most-adopted is Alacritty at 66,108 stars.
Are these gpu projects free to use?
Yes — 10 of the 10 carry an explicit open-source licence across 4 distinct licences, so there is no licence fee. Where a project also sells a hosted or enterprise version, the self-hosted path remains free.
Which gpu project should I choose?
The list above is ranked by GitHub stars, but stars measure attention rather than fit. Check three things on each card: the licence (permissive versus copyleft), the language it is written in, and the last-push date — a high-star project that has not been pushed in a year is a liability.
Are these gpu projects still maintained?
10 of the 10 were pushed in the last 90 days, and every card shows its exact last-push date so you can see the rest. Sort your shortlist by that date before committing to a migration.