What are Cloud GPUs?
Cloud GPUs are NVIDIA accelerators attached to Compute Engine VMs. They accelerate machine learning, scientific computing, and other GPU-intensive applications. The portfolio ranges from cost-effective T4 and L4 GPUs to A100 and H100/H200, up to the latest Blackwell-based B200 and GB200 systems for foundation model training.
Core Features
- Broad NVIDIA GPU portfolio: T4, L4, A100, H100/H200, and the current Blackwell generation (B200/GB200) for different requirements
- Flexible configuration: Multiple GPUs per VM, depending on machine type and series
- Deep Learning VMs: Pre-configured images with CUDA, cuDNN, and common ML frameworks
- Spot/Preemptible VMs: Significant cost savings for interruptible training jobs
- Multi-Instance GPU: Supported GPU types can be partitioned into multiple isolated instances
Typical Use Cases
Large-Scale ML Training
Train large models with A100, H100/H200, or Blackwell GPUs. Multi-GPU and multi-node training for faster iterations.
Real-Time AI Inference
Low-latency inference for computer vision, NLP, or recommendation models. T4 and L4 offer good price-performance for inference workloads.
Batch Rendering and Simulation
Video rendering, 3D visualization, and scientific simulations on scalable GPU infrastructure.
Benefits
- Broad GPU portfolio for a wide range of use cases
- No hardware investment needed
- Fast provisioning and scaling
- Integration with the Gemini Enterprise Agent Platform and other ML services
Integration with innFactory
As a certified Google Cloud Partner, innFactory supports you with Cloud GPUs: GPU selection, cost optimization, training pipeline architecture, and MLOps integration.
Available Tiers & Options
NVIDIA L4 / T4
- Cost-effective inference
- Good regional availability
- Limited training performance for large models
NVIDIA A100
- High training performance
- Large memory (40/80 GB)
- Older generation, availability varies by region
NVIDIA H100 / H200
- Very high performance for training and inference
- Transformer Engine
- Premium pricing
- Limited regional availability
NVIDIA B200 / GB200 (Blackwell)
- Latest generation for foundation model training
- Very high scalability in clusters
- Available only in select regions and quotas
Typical Use Cases
Frequently Asked Questions
Which GPU types does Google Cloud offer?
Google Cloud offers a broad NVIDIA portfolio ranging from T4 and L4 to A100, H100/H200, and the latest Blackwell-based B200 and GB200 accelerators. Availability varies by region and machine series.
How do GPUs differ from TPUs?
GPUs are universally usable for ML training, inference, and other workloads. TPUs are Google's own accelerators, optimized for specific frameworks and often more efficient for very large models.
Are GPUs available in EU regions?
Yes, most GPU types are also available in European regions. Which GPU generation is offered in which region should be checked in the current availability overview before planning.
How are GPUs billed?
GPUs are billed on a usage basis, typically per hour or per second of use. Spot and preemptible VMs offer significant discounts for interruptible workloads.
Can I use GPUs with the Gemini Enterprise Agent Platform?
Yes, the Gemini Enterprise Agent Platform (formerly Vertex AI) automatically uses suitable GPU or TPU resources in the background for training and prediction. Custom training jobs can also request specific GPU types.
Note: All product information on this page has been compiled with care, but is provided without guarantee and may be outdated or incomplete. Cloud services evolve rapidly — features, pricing, SLAs, and availability change frequently. Authoritative and up-to-date information can only be found on the official product page of Google Cloud (official documentation). This page does not represent an offer by Google Cloud.
