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Compare GPU and LLM inference API pricing between Google Cloud and TensorDock. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
Average Price Difference: $0.95/hour between comparable GPUs
| GPU Model ↑ | Google Cloud Price | TensorDock Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 PCIE 40GB VRAM • TensorDock | Not Available | 8x GPU | — | |
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • TensorDock | Not Available | 4x GPU | — | |
A100 SXM 80GB VRAM • | ||||
A40 48GB VRAM • TensorDock | Not Available | — | ||
A40 48GB VRAM • | ||||
H100 SXM 80GB VRAM • TensorDock | Not Available | 4x GPU | — | |
H100 SXM 80GB VRAM • | ||||
L4 24GB VRAM • TensorDock | Not Available | — | ||
L4 24GB VRAM • | ||||
L40 40GB VRAM • TensorDock | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • TensorDock | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX 3080 Ti 12GB VRAM • TensorDock | Not Available | 2x GPU | — | |
RTX 3080 Ti 12GB VRAM • | ||||
RTX 3090 24GB VRAM • TensorDock | Not Available | 2x GPU | — | |
RTX 3090 24GB VRAM • | ||||
RTX 4080 16GB VRAM • TensorDock | Not Available | 2x GPU | — | |
RTX 4080 16GB VRAM • | ||||
RTX 4090 24GB VRAM • TensorDock | Not Available | 5x GPU | — | |
RTX 4090 24GB VRAM • | ||||
RTX 5090 32GB VRAM • TensorDock | Not Available | — | ||
RTX 5090 32GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • TensorDock | Not Available | 3x GPU | — | |
RTX 6000 Ada 48GB VRAM • | ||||
RTX A4000 16GB VRAM • TensorDock | Not Available | 2x GPU | — | |
RTX A4000 16GB VRAM • | ||||
RTX A5000 24GB VRAM • TensorDock | Not Available | — | ||
RTX A5000 24GB VRAM • | ||||
A100 PCIE 40GB VRAM • TensorDock | Not Available | 8x GPU | — | |
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • TensorDock | Not Available | 4x GPU | — | |
A100 SXM 80GB VRAM • | ||||
A40 48GB VRAM • TensorDock | Not Available | — | ||
A40 48GB VRAM • | ||||
H100 SXM 80GB VRAM • TensorDock | Not Available | 4x GPU | — | |
H100 SXM 80GB VRAM • | ||||
L4 24GB VRAM • TensorDock | Not Available | — | ||
L4 24GB VRAM • | ||||
L40 40GB VRAM • TensorDock | Not Available | — | ||
L40 40GB VRAM • | ||||
L40S 48GB VRAM • TensorDock | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX 3080 Ti 12GB VRAM • TensorDock | Not Available | 2x GPU | — | |
RTX 3080 Ti 12GB VRAM • | ||||
RTX 3090 24GB VRAM • TensorDock | Not Available | 2x GPU | — | |
RTX 3090 24GB VRAM • | ||||
RTX 4080 16GB VRAM • TensorDock | Not Available | 2x GPU | — | |
RTX 4080 16GB VRAM • | ||||
RTX 4090 24GB VRAM • TensorDock | Not Available | 5x GPU | — | |
RTX 4090 24GB VRAM • | ||||
RTX 5090 32GB VRAM • TensorDock | Not Available | — | ||
RTX 5090 32GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • TensorDock | Not Available | 3x GPU | — | |
RTX 6000 Ada 48GB VRAM • | ||||
RTX A4000 16GB VRAM • TensorDock | Not Available | 2x GPU | — | |
RTX A4000 16GB VRAM • | ||||
RTX A5000 24GB VRAM • TensorDock | Not Available | — | ||
RTX A5000 24GB VRAM • | ||||
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.
Short-lived compute instances at a significant discount, suitable for fault-tolerant workloads.
Root access and dedicated GPUs with full OS control, manage your own drivers and Windows 10 support
100+ locations across 20+ countries with enterprise-grade servers in tier 3/4 data centers
Continuous billing with automatic server deletion when balance reaches zero
Well-documented REST API for programmatic server management with metadata and availability
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.
High-performance CPU instances with latest Intel Xeon and AMD EPYC processors
Pay for compute capacity per hour or per second, with no long-term commitments.
Automatic discounts for running instances for a significant portion of the month.
Save up to 57% with a 1-year or 3-year commitment to a minimum level of resource usage.
Save up to 80% for fault-tolerant workloads that can be interrupted.
Per-second billing with automatic server deletion when balance reaches zero
Long-term rental options available for enterprise customers
Independent hosts compete and set their own pricing for best market rates
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.
Register in just two clicks with email or GitHub account
Start with as little as $5 deposit for pay-as-you-go billing
Run your workload on enterprise-grade hardware in 30 seconds
40+ regions and 120+ zones worldwide.
Role-based (free), Standard, Enhanced and Premium support plans. Comprehensive documentation, community forums, and training resources.
100+ locations across 20+ countries with enterprise-grade servers in tier 3/4 data centers
24/7 staff availability with 24-hour response time standard, Discord community, comprehensive documentation