Cloud Tensor Processing Units (TPUs)
Accelerate AI development with Google Cloud TPUs
Not sure if TPUs are the right fit? Learn about when to use GPUs or CPUs on Compute Engine instances to run your machine learning workloads.
Overview
What is a Tensor Processing Unit (TPU)?
What are the advantages of Cloud TPUs?
When to use Cloud TPUs?
How are Cloud TPUs different from GPUs?
A GPU is a specialized processor originally designed for manipulating computer graphics. Their parallel structure makes them ideal for algorithms that process large blocks of data commonly found in AI workloads. Learn more.
A TPU is an application-specific integrated circuit (ASIC) designed by Google for neural networks. TPUs possess specialized features, such as the matrix multiply unit (MXU) and proprietary interconnect topology that make them ideal for accelerating AI training and inference.
Cloud TPU versions
Cloud TPU v5p
The most powerful Cloud TPU for training AI models
Cloud TPU v5p will be available in North America (US East region)
Cloud TPU v5e
The most efficient, versatile, and scalable Cloud TPU
Cloud TPU v5e is generally available in North America (US West/East regions)
Cloud TPU version | Description | Availability |
---|---|---|
Cloud TPU v5p |
The most powerful Cloud TPU for training AI models |
Cloud TPU v5p will be available in North America (US East region) |
Cloud TPU v5e |
The most efficient, versatile, and scalable Cloud TPU |
Cloud TPU v5e is generally available in North America (US West/East regions) |
How It Works
Get an inside look at the magic of Google Cloud TPUs, including a rare inside view of the data centers where it all happens. Customers use Cloud TPUs to run some of the world's largest AI workloads and that power comes from much more than just a chip. In this video, take a look at the components of the TPU system, including data center networking, optical circuit switches, water cooling systems, biometric security verification and more.
Common Uses
Run large-scale AI training workloads
Powerful, scalable, and efficient AI training
Cloud TPU Multislice training is a full-stack
technology that enables fast, easy, and
reliable large-scale AI model training across
tens of thousands of TPU chips.
Fine-tune foundational AI models
Serve large-scale AI inference workloads
Maximize performance/$ with AI infrastructure that scales
Cloud TPU v5e enables high-performance and
cost-effective inference for a wide range of
AI workloads, including the latest LLMs and
Gen AI models. TPU v5e delivers up to 2.x more
throughput performance per dollar and up to
1.7x speedup over Cloud TPU v4. Each TPU v5e
chip provides up to 393 trillion int8
operations per second, allowing complex models
to make fast predictions. A TPU v5e pod
delivers up to 100 quadrillion int8 operations
per second, or 100 petaOps of compute power.
Cloud TPU in GKE
Effortless scaling with GKE
Combine the power of Cloud TPUs with the
flexibility and scalability of
GKE
to build and deploy machine learning models
faster and more easily than ever before. With
Cloud TPUs available in GKE, you can now have
a single consistent operations environment for
all your workloads, standardizing automated
MLOps pipelines.
Cloud TPU in Vertex AI
Vertex AI Training & Predictions with Cloud TPUs
For customers looking for a simplest way to
develop AI models, you can deploy Cloud TPU v5e
with
Vertex AI,
an end-to-end platform for building AI models on
fully-managed infrastructure that’s purpose-built
for low-latency serving and high-performance
training.
Pricing
Cloud TPU pricing
All Cloud TPU pricing is per chip-hour
$4.2000
per chip-hour
$2.9400
per chip-hour
$1.8900
per chip-hour
Cloud TPU v5e
$1.2000
per chip-hour
$0.8400
per chip-hour
$0.5400
per chip-hour
Cloud TPU pricing | All Cloud TPU pricing is per chip-hour | ||
---|---|---|---|
Cloud TPU Version | Evaluation Price (USD) | 1-year commitment (USD) | 3-year commitment (USD) |
Cloud TPU v5p |
$4.2000 per chip-hour |
$2.9400 per chip-hour |
$1.8900 per chip-hour |
Cloud TPU v5e |
$1.2000 per chip-hour |
$0.8400 per chip-hour |
$0.5400 per chip-hour |