Qualcomm

About Qualcomm

Qualcomm provides an on-device AI platform designed for mobile, edge, and embedded hardware, enabling efficient inference where latency, privacy, and power efficiency are critical. The platform combines optimized silicon, software toolchains, and connectivity to deploy intelligent experiences at scale. It supports real-time processing for voice and vision applications while maintaining low power consumption and preserving user privacy by keeping data on device. Typical workflows involve importing trained models, quantizing and compiling them for target hardware, integrating with application code, and validating performance through profiling tools. The platform is tailored for product teams building latency-sensitive features, such as mobile OEMs, wearable manufacturers, automotive engineers, and industrial IoT integrators. It also serves researchers and ML engineers who need to validate models on actual hardware early, aligning architectures to real-world constraints like memory and bandwidth. By balancing workloads across CPU, GPU, and dedicated accelerators, Qualcomm ensures high performance per watt, enabling responsive and context-aware experiences even under varying network conditions. Continuous testing, feature flagging, and over-the-air updates help maintain consistent performance across diverse device tiers without compromising battery life or user experience.

Key features

• ✓Compile and optimize trained models for low-latency execution on target hardware
• ✓Balance workloads across CPU, GPU, and dedicated accelerators for performance per watt
• ✓Quantize, fuse, and prune operations while preserving accuracy under practical constraints
• ✓Integrate AI features with sensors and connectivity for responsive, context-aware experiences
• ✓Profile latency, power, and memory to guide deployment and updates
• ✓Enable real-time on-device inference for voice and vision applications
• ✓Support seamless cloud coordination over 5G or Wi‑Fi when needed
• ✓Provide model conversion, quantization, profiling, and packaging workflows
• ✓Deliver power-efficient AI optimized for mobile and edge devices
• ✓Ensure privacy-first processing by keeping sensitive data on device

Use cases

• ✓Deploying wake-word detection and voice assistants on mobile devices with minimal latency
• ✓Enabling real-time camera-based object detection and segmentation in automotive systems
• ✓Building predictive maintenance features for industrial IoT devices with on-device AI

Frequently asked questions about Qualcomm