Deploy TensorFlow on Google Cloud C4A (Arm-based Axion VMs)
Introduction
Get started with TensorFlow on Google Axion C4A
Create a Google Axion C4A Arm virtual machine on GCP
Install TensorFlow
Test TensorFlow baseline performance on Google Axion C4A
Benchmark TensorFlow model performance using tf.keras
Next Steps

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About this Learning Path

Skill level:  Introductory
Reading time:  30 min
Last updated:  31 Jul 2026
Skill level:
  Introductory
Reading time:
  30 min
Last updated:
  31 Jul 2026
Author:Pareena Verma, Arm
Arm IP:Neoverse
Tags: ML Google Cloud Linux TensorFlow Python Keras
Author:
  • Pareena Verma, Arm
Arm IP:
Neoverse
Tags:
ML Google Cloud Linux TensorFlow Python Keras

Who is this for?

This is an introductory topic for software developers deploying and optimizing TensorFlow workloads on Arm64 Linux environments, specifically using Google Cloud C4A virtual machines powered by Axion processors.

What will you learn?

Upon completion of this Learning Path, you will be able to:

  • Provision an Arm-based SUSE Linux Enterprise Server (SLES) virtual machine on Google Cloud (C4A with Axion processors)
  • Install TensorFlow on a SUSE Arm64 (C4A) instance
  • Verify TensorFlow by running basic computation and model training tests on Arm64
  • Benchmark TensorFlow using TensorFlow Keras (`tf.keras`) to evaluate inference speed and model performance on Arm64 systems

Prerequisites

Before starting, you will need the following:

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