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Compare GPU and LLM inference API pricing between Google Cloud and Zettabyte. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | Google Cloud Price | Zettabyte Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 SXM 80GB VRAM • Google Cloud | 16x GPU | Not Available | — | |
A100 SXM 80GB VRAM • | ||||
B200 180GB VRAM • Google Cloud | 8x GPU | Not Available | — | |
B200 180GB VRAM • | ||||
H100 SXM 80GB VRAM • Zettabyte | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Google Cloud | 8x GPU | Not Available | — | |
H200 141GB VRAM • | ||||
L4 24GB VRAM • Google Cloud | 2x GPU | Not Available | — | |
L4 24GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • Google Cloud | Not Available | — | ||
RTX PRO 6000 96GB VRAM • | ||||
A100 SXM 80GB VRAM • Google Cloud | 16x GPU | Not Available | — | |
A100 SXM 80GB VRAM • | ||||
B200 180GB VRAM • Google Cloud | 8x GPU | Not Available | — | |
B200 180GB VRAM • | ||||
H100 SXM 80GB VRAM • Zettabyte | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Google Cloud | 8x GPU | Not Available | — | |
H200 141GB VRAM • | ||||
L4 24GB VRAM • Google Cloud | 2x GPU | Not Available | — | |
L4 24GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • Google Cloud | Not Available | — | ||
RTX PRO 6000 96GB VRAM • | ||||
| Model ↑ | Google Cloud | Zettabyte | Input Diff ↕ |
|---|---|---|---|
Google | $0.150 in $0.600 out | Not available | — |
Google | $0.075 in $0.300 out | Not available | — |
Google | $0.300 in $2.50 out | Not available | — |
Google | $0.100 in $0.400 out | Not available | — |
Google | $1.25 in $10.00 out | Not available | — |
Google | $0.500 in $3.00 out | Not available | — |
Google | $0.250 in $1.50 out | Not available | — |
Google | $2.00 in $12.00 out | Not available | — |
Google | $1.50 in $9.00 out | Not available | — |
Google | $0.300 in $2.50 out | Not available | — |
Google | $0.750 in $3.75 out | Not available | — |
Google | $0.750 in $3.75 out | Not available | — |
Google | $0.750 in $3.75 out | Not available | — |
Explore how these providers compare to other popular GPU cloud services
Compare Google Cloud with another leading provider
Compare Google Cloud with another leading provider
Compare Google Cloud with another leading provider
Compare Google Cloud with another leading provider
Compare Google Cloud with another leading provider
Compare Google Cloud with another leading provider
Scalable virtual machines with a wide range of machine types, including GPUs.
Managed Kubernetes service for deploying and managing containerized applications.
Event-driven serverless compute platform.
Fully managed serverless platform for containerized applications.
Unified ML platform for building, deploying, and managing ML models.
Spare compute capacity at discounted Spot prices, suitable for fault-tolerant workloads that can be interrupted.
Launch GPU instances quickly and scale to hundreds on-demand.
Designed for large-scale training with predictable capacity.
Custom clusters tailored for specific security and procurement needs.
Utilizes a bid/ask system to ensure optimal pricing on GPU resources.
Ensures 99.9% uptime SLA with transparent incident reporting.
Offers customizable virtual machines running in Google's data centers.
Managed Kubernetes service for running containerized applications.
Serverless compute platform for running code in response to events.
Pay for vCPUs, GPUs, and memory with a one-minute minimum and per-second billing thereafter, with no long-term commitments.
Automatic discounts for running instances for a significant portion of the month.
Discounted rates in exchange for a 1-year or 3-year commitment to a minimum level of resource usage in a region, and combinable with reservations.
Spend-based commitments that apply across eligible machine families and regions rather than to specific resources.
Spare capacity at discounted Spot prices for fault-tolerant workloads that can be preempted.
Set up a project in the Google Cloud Console.
Set up a billing account to pay for resource usage.
Select Compute Engine, GKE, Cloud Functions, or Cloud Run based on your needs.
Launch a VM instance, configure a Kubernetes cluster, or deploy a function/application.
Use the Cloud Console, command-line tools, or APIs to manage your resources.
Access the main platform to explore available services.
Select between on-demand, reserved clusters, or private cloud.
Provide necessary information to create a user account.
Fill in details for account management and payment.
Follow prompts to deploy your chosen compute resource.
40+ regions and 120+ zones worldwide.
Role-based (free), Standard, Enhanced and Premium support plans. Comprehensive documentation, community forums, and training resources.