PhyAI 是一个用于运行 Physical AI 模型（VLA、WAM 等）的高性能框架，支持云端推理服务和端侧部署。
PhyAI (pronounced "phi") is a latency-first serving engine for Physical AI. It is designed first for latency critical workloads, such as policy and action models that run in interactive systems.
News
- [2026/07] 🚀 Day 0 support for MiniCPM-Robotic blog.
- [2026/07] 👏 Introducing PhyAI, a latency-first serving engine for Physical AI. Read the Blog.
- [2026/07] Support PI0.
- [2026/07] Support Cosmos3-Super with TP and CFG parallelism in the unified Cosmos3 generation path.
- [2026/06] Support Pi0.5 and Cosmos3-Nano's policy mode and generation mode.
Key Features
- 🚀 Runs on NVIDIA Jetson edge devices
- 🚀 Scales to GPU clusters with DP, TP, and CFG parallelism
- 🚀 Uses high-performance kernels from FlashInfer and Humming
- 🤗 Supports W4A8 (NVFP4, MXFP4, INT4), W8A8, and W8A16 quantization (PR under review)
Supported Models
| VLA | π0, π0.5(w/ DP), GR00T N1.7, MiniCPM-Robot |
|---|---|
| WAM | Cosmos3-Nano-Policy-DROID(w/ TP, CFG Parallel) |
| Foundation Model | Cosmos3-Nano(w/ TP, CFG Parallel), Cosmos3-Super(w/ TP, CFG Parallel), Qwen3.5, Qwen3-VL |
Performance Comparison
Installation
See the PhyAI installation guide for the latest source and nightly package instructions.
From source:
git clone https://github.com/mingti-org/phyai
cd phyai
uv sync
Nightly build:
uv pip install phyai phyai-ext \
--extra-index-url https://mingti-org.github.io/phyai/simple/ \
--prerelease=allow
Contribution Guidelines
We thank the contributors below and welcome more developers to join us in building PhyAI.
Sponsors & Adoption
PhyAI is a latency-first, open-source serving engine for Physical AI. It is being adopted by companies working across AI infrastructure and robotics, including Mingti and ModelBest.
We are actively seeking partnerships with compute providers, chip vendors, and robotics companies. If you are interested in working with us, please contact us.
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Citation
If you use PhyAI in research or production work, please cite the project:
@software{phyai2026,
title = {PhyAI: Latency-First Serving Engine for Physical AI},
author = {{PhyAI Team}},
year = {2026},
url = {https://github.com/mingti-org/phyai}
}
We welcome PhD and master's students who want to help build Physical AGI, especially those interested in systems infrastructure. We also want to work with chip and compute companies, as well as robotics companies that plan to deploy models with PhyAI.
- PhyAI: Maintainer
- Mengwei Xu: mwx@bupt.edu.cn
- Daliang Xu: xudaliang@bupt.edu.cn
License
PhyAI is released under the MIT License. It uses FlashInfer, Humming, and FLA. We have also learned a great deal from SGLang, vLLM, and TokenSpeed. We thank the maintainers and contributors of all these projects.
Demos
Cosmos3-Nano-Policy-DROID, 260718 nightly version
https://github.com/user-attachments/assets/12a833ce-3b47-4f08-875c-b30cc2567bef
https://github.com/user-attachments/assets/8e7d433c-e3b1-4388-8488-196836a1ba51
https://github.com/user-attachments/assets/29067c88-f51a-4ca6-ab8c-b45f4d778923