At Qualcomm Technologies, Inc., we transform how the world connects, computes and communicates. We are on a journey to embrace open source, its upstream contribution model and industry standards to make it easy for developers to innovate, build and scale.
Featured on-device AI projects
AI Model Efficiency Toolkit (AIMET): Advanced quantization and compression techniques to optimize trained neural networks for efficient inference
GenieX SDK: A high‑performance on-device inference framework that runs the latest multimodal models locally on NPU/GPU/CPU across common platforms
Qualcomm® AI Hub Models: A collection of deployment-ready ML models optimized for on-device performance and ready to run on Qualcomm devices
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Qualcomm branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries. AIMET and AudioReach are products of Qualcomm Innovation Center, Inc.
Qualcomm® AI Hub Models is our collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.
The Qualcomm® AI Hub apps are a collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.
QAI AppBuilder is designed to help developers easily execute models on WoS and Linux platforms. It encapsulates the Qualcomm® AI Runtime SDK APIs into a set of simplified interfaces for running mod…
Official QEMU mirror. Please see http://wiki.qemu.org/Contribute/SubmitAPatch for how to submit changes to QEMU. Pull Requests are ignored. Please only use release tarballs from the QEMU website.
QAI AppBuilder is designed to help developers easily execute models on WoS and Linux platforms. It encapsulates the Qualcomm® AI Runtime SDK APIs into a set of simplified interfaces for running models on the NPU/HTP.
qualcomm/qai-appbuilder's past year of commit activity
Qualcomm® AI Hub Models is our collection of state-of-the-art machine learning models optimized for performance (latency, memory etc.) and ready to deploy on Qualcomm® devices.
qualcomm/ai-hub-models's past year of commit activity
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