ZETIC × Qualcomm: Unlocking the NPU Era for Every Developer

The future of AI isn't in the cloud. It is in the palm of your hand, in your car, and embedded in the world around you. But getting high-performance AI to run locally on edge devices has historically been a fragmented, painful process for developers.

Today, we are thrilled to announce that ZETIC is collaborating with Qualcomm to change that. We are bringing seamless, zero-friction on-device AI deployment to Qualcomm's industry-leading platforms.

From Qualcomm to ZETIC: Building What We Needed

Our founder, Yeonseok Kim, didn't just watch the on-device AI revolution happen; he spent years engineering it from the inside as a Senior ML Engineer with the Qualcomm AI Research team.

From developing real-time embedded neural network frameworks for resource-constrained NPUs (which saw commercialization into products like Amazon Alexa, Meta Oculus, and Samsung Bixby) to eventually building Qualcomm's company-wide AI development platform, his mandate was clear: build the high-level abstraction layers that allow developers to deliver machine learning solutions without getting bogged down in low-level memory optimizations, fully quantized networks, or hardware-specific APIs.

Through this hands-on work, he saw the industry's biggest disconnect firsthand. While mobile and edge silicon was advancing at breakneck speed, the software tooling for the broader developer community to actually use that hardware was painfully far behind. Building for the edge still meant wrestling with complex integrations and weeks of manual fine-tuning.

ZETIC was born from this exact frustration. We built a general AI infrastructure platform that strips away the complexity, allowing developers to deploy optimized AI models directly to edge devices with the simplicity of a standard API call.

The NPU-First Future

While CPUs and GPUs paved the way for early AI and still deliver superior performance for certain workloads, the frontier for high-efficiency on-device inference is the Neural Processing Unit (NPU).

Through this collaboration, ZETIC is integrating its deployment technology seamlessly with Qualcomm's state-of-the-art Hexagon™ NPUs. We are enabling deployment across a wide range of environments, from mobile to compute to automotive platforms, including platforms like the Snapdragon® 8 Elite Gen 5 (mobile) and the Snapdragon® X2 Elite (compute).

By routing appropriate workloads directly to the NPU, developers can bypass traditional compute bottlenecks, achieving massive gains in inference speed and significant reductions in energy consumption on specific optimized models.

We aren't just exploring edge AI. We are actively enabling developers to tap into this dedicated silicon. What used to take an ML engineering team weeks of low-level optimization can now be executed by a single developer in minutes. Migrating that deployment to an entirely different hardware platform requires only a few additional minutes.

Evaluating Hardware Performance & Choosing the Right Model

Benchmarks serve two critical roles for developers: checking how an AI architecture performs on different hardware to choose the right target, and comparing different architectures to select the best fit for an application.

To provide a realistic baseline for these decisions, we tested several widely adopted, industry-standard AI models available directly through the ZETIC public library. Here is a look at the performance profiles when evaluating these workloads, comparing standard on-device CPU execution against the dedicated Hexagon NPU powered by ZETIC:

(Note: For Qwen3.5 and Liquid AI, times represent TTFT or Time To First Token. For Amazon Chronos 2, times represent total Inference Time. For YOLO26n, FPS stands for Frames Per Second. Lower milliseconds and higher FPS indicate better performance.)

By understanding these exact performance leaps, engineering teams can confidently optimize for latency and throughput to ensure they deliver a highly responsive, real-time user experience.

Empowering the Builder Ecosystem

Great infrastructure is nothing without the developers who build on it. A massive pillar of our collaboration with Qualcomm is supporting the developer ecosystem.

We want to move past whitepapers and get directly into the trenches with the community. In the coming months, ZETIC and Qualcomm are exploring ways to introduce:

• Global AI Hackathons: Build the next generation of real-time, privacy-first apps using the ZETIC toolchain on Qualcomm hardware.

• Hands-on Engineering Workshops: Deep dives into NPU optimization, showing you exactly how to port your models to the edge with zero friction.

• Open-Source Templates: Production-ready code snippets so you can go from idea to on-device prototype in under an hour.

Build for the Edge, Today

The era of relying solely on expensive, latency-heavy cloud compute is over. ZETIC and Qualcomm are equipping developers with the tools to build faster, cheaper, and highly performant on-device AI applications.