Open source gpu projects
Every project in the registry tagged gpu, ranked by real GitHub adoption.
High-performance terminal with GPU acceleration
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
Serverless GPU compute with sub-second cold starts
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™
🔥 Real-time NVIDIA GPU dashboard
Pure Rust + CUDA LLM inference engine — no PyTorch, OpenAI-compatible, serves Qwen3 to Kimi-K2
Related tags
Frequently asked questions
How many open source gpu projects are there?
This registry tracks 8 projects tagged gpu, with 79,505 GitHub stars between them. The most-adopted is Alacritty at 65,752 stars.
Are these gpu projects free to use?
Yes — 8 of the 8 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?
8 of the 8 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.