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PhyAI

Blog Docs GitHub License open issues Nightly


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.

PhyAI and OpenPI deployment comparison

News

  • [2026/07] πŸš€ Day 0 support for MiniCPM-Robotic blog.
  • [2026/07] πŸ‘ 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

  • πŸš€ Runs on NVIDIA Jetson edge devices
  • πŸš€ Scales to GPU clusters with DP, TP, and CFG parallelism
  • πŸš€ Uses high-performance kernels from FlashInfer and Humming
  • πŸ€— Supports W4A8 (NVFP4, MXFP4, INT4), W8A8, and W8A16 quantization (PR under review)

Supported Models

VLA Ο€0, Ο€0.5(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

Bar chart comparing PhyAI and official single-request latency across supported models and devices

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.

Mingti ModelBest

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}
}

Contact:

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.

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

f5355783789c3101e7a7747f16c731b0.mp4
5b2dedee8fa8a683b88131c4875fd45e.mp4
4e4a4ab48b05708408aa41bccbb51c4b.mp4

About

PhyAI is a high-performance framework for running Physical AI models (VLA, WAM, and beyond), supporting both cloud-based serving and on-device deployment.

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