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Compare GPU and LLM inference API pricing between Google Cloud and TensorWave. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | Google Cloud Price | TensorWave Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
MI300X 192GB VRAM • TensorWave | Not Available | — | ||
MI300X 192GB VRAM • | ||||
MI325X 256GB VRAM • TensorWave | Not Available | — | ||
MI325X 256GB VRAM • | ||||
MI355X 288GB VRAM • TensorWave | Not Available | — | ||
MI355X 288GB VRAM • | ||||
Tesla T4 16GB VRAM • Google Cloud | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • Google Cloud | Not Available | — | ||
Tesla V100 32GB VRAM • | ||||
MI300X 192GB VRAM • TensorWave | Not Available | — | ||
MI300X 192GB VRAM • | ||||
MI325X 256GB VRAM • TensorWave | Not Available | — | ||
MI325X 256GB VRAM • | ||||
MI355X 288GB VRAM • TensorWave | Not Available | — | ||
MI355X 288GB VRAM • | ||||
Tesla T4 16GB VRAM • Google Cloud | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • Google Cloud | Not Available | — | ||
Tesla V100 32GB 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.
Powered by AMD Instinct™ Series GPUs including MI355X, MI325X, and MI300X for high-performance AI workloads.
Offers instances with up to 288GB of HBM3e VRAM per GPU, ideal for large models and memory-intensive workloads.
Provides both bare metal servers for maximum control and managed Kubernetes/Slurm clusters for orchestration.
Utilizes direct liquid cooling delivering up to 51% data center energy cost savings and improved efficiency.
Complete architecture that optimizes next-generation Ethernet for AI and HPC networking with high-speed storage.
SOC2 Type II certified and HIPAA compliant infrastructure for secure AI workloads.
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.
Bare metal servers and managed Kubernetes clusters with AMD Instinct GPUs.
Kubernetes clusters for orchestrated AI workloads.
An enterprise inference platform designed for larger context windows and reduced latency.
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.
Guaranteed availability with full root access and transparent hourly pricing for MI355X, MI325X, and MI300X GPUs
Custom pricing for multi-node clusters with tailored networking configurations
Custom pricing for high-performance storage powered by Weka file system
Predictable costs without tokenized pricing models or hidden fees
Reduced costs for long-term contracts and high-volume usage commitments
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.
Sign up on the TensorWave website to get access to their platform.
Select between Bare Metal servers or a managed Kubernetes cluster.
Utilize the documentation and quick-start guides for PyTorch, Docker, Kubernetes, and other tools.
Deploy your AI model for training, fine-tuning, or inference.
40+ regions and 120+ zones worldwide.
Role-based (free), Standard, Enhanced and Premium support plans. Comprehensive documentation, community forums, and training resources.
Primary data center and headquarters are located in Las Vegas, Nevada. The company is building the largest AMD-specific AI training cluster in North America.
Offers 'white-glove' onboarding and 24/7 dedicated AI/ML solutions engineers, extensive documentation with quickstart guides, and enterprise-grade support.