Google Axion C4A is a family of Arm-based virtual machines built on Google’s custom Axion CPU, which is based on Arm Neoverse-V2 cores. Designed for high-performance and energy-efficient computing, these virtual machines offer strong performance for modern cloud workloads such as CI/CD pipelines, microservices, media processing, and general-purpose applications.
The C4A series provides a cost-effective alternative to x86 virtual machines while using the scalability and performance benefits of the Arm architecture in Google Cloud.
To learn more, see the Google blog Introducing Google Axion Processors, our new Arm-based CPUs .
Open Source Computer Vision Library (OpenCV) is an open-source library for real-time computer vision and image processing applications. It includes implementations for image transforms, video processing, object detection, and integration with machine learning models.
When you run OpenCV on Google Axion C4A infrastructure, you can use multi-core CPU parallelism to scale image and video workloads on Arm. In practice, this helps you:
Common use cases include real-time video analytics, image transformation pipelines, automated inspection systems, and ML-powered vision applications.
To learn more, see the OpenCV documentation and explore the OpenCV GitHub repository .
You’ve now reviewed what Google Axion C4A instances provide on Arm and why they are a good fit for OpenCV workloads. You also mapped OpenCV capabilities to practical cloud use cases you can run on C4A.
Next, you’ll create a firewall rule so you can view OpenCV pipeline output from your browser while your application runs on an Arm-based virtual machine.