What is the difference between IBM Cloud and TensorWave?

IBM Cloud and TensorWave are both cloud GPU providers offering different pricing models, features, and GPU availability. Use our comparison tool to see real-time pricing and feature differences.

Which is cheaper: IBM Cloud or TensorWave?

Pricing varies by GPU model and usage requirements. Check our real-time comparison table to find the best deals for your specific needs.

Can I switch between IBM Cloud and TensorWave?

Yes, both providers offer flexible cloud GPU services. However, consider factors like data transfer costs, setup time, and specific features when switching between providers.

How many GPU models are available for comparison?

We track pricing for 2 different GPU models across both IBM Cloud and TensorWave, with 0 models available from both providers.

IBM Cloud vs TensorWave

Compare GPU pricing, features, and specifications between IBM Cloud and TensorWave cloud providers. Find the best deals for AI training, inference, and ML workloads.

IBM Cloud

Provider 1

GPUs Available

Visit Website

TensorWave

Provider 2

GPUs Available

Visit Website

Comparison Overview

Total GPU Models

IBM Cloud GPUs

TensorWave GPUs

Direct Comparisons

View:

IBM Cloud

TensorWave

GPU Pricing Comparison

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Features Comparison

IBM Cloud

TensorWave

AMD Instinct Accelerators
Powered by AMD Instinct™ Series GPUs for high-performance AI workloads.
High VRAM GPUs
Offers instances with 192GB of VRAM per GPU, ideal for large models.
Bare Metal & Kubernetes
Provides both bare metal servers for maximum control and managed Kubernetes for orchestration.
Direct Liquid Cooling
Utilizes direct liquid cooling to reduce data center energy costs and improve efficiency.
High-Speed Network Storage
Features high-speed network storage to support demanding AI pipelines.
ROCm Software Ecosystem
Leverages the AMD ROCm open software ecosystem to avoid vendor lock-in.

Pros & Cons

IBM Cloud

Advantages

Strong focus on AI and data workloads
Enterprise-grade support
Integration with IBM's AI tools

Considerations

Limited global presence compared to competitors
Higher cost for some services
Less community support

TensorWave

Advantages

Specialized in high-performance AMD GPUs
Offers GPUs with large VRAM (192GB)
Claims better price-to-performance than competitors
Provides 'white-glove' onboarding and support

Considerations

A newer and less established company (founded in 2023)
Exclusively focused on AMD, which may be a limitation for some users
Limited publicly available information on pricing

Compute Services

IBM Cloud

TensorWave

AMD GPU Instances

Bare metal servers and managed Kubernetes clusters with AMD Instinct GPUs.

Managed Kubernetes

Kubernetes clusters for orchestrated AI workloads.

Scalable from 8 to 1024 GPUs
Interconnected with 3.2TB/s RoCE v2 networking

Inference Platform (Manifest)

An enterprise inference platform designed for larger context windows and reduced latency.

Accelerated reasoning
Secure and private data storage

Pricing Options

IBM Cloud

TensorWave

Getting Started

IBM Cloud

Get Started

TensorWave

Get Started

1
Request Access
Sign up on the TensorWave website to get access to their platform.
2
Choose a Service
Select between Bare Metal servers or a managed Kubernetes cluster.
3
Follow Quickstarts
Utilize the documentation and quick-start guides for PyTorch, Docker, Kubernetes, and other tools.
4
Deploy Your Model
Deploy your AI model for training, fine-tuning, or inference.

Support & Global Availability

IBM Cloud

TensorWave

Global Regions

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.

Support

Offers 'white-glove' onboarding and support, extensive documentation, and a company blog.