Hot Aisle vs TensorWave
Compare GPU pricing, features, and specifications between Hot Aisle and TensorWave cloud providers. Find the best deals for AI training, inference, and ML workloads.
Hot Aisle
Provider 1

TensorWave
Provider 2
Comparison Overview

Average Price Difference: $1.50/hour between comparable GPUs
GPU Pricing Comparison
Features Comparison
Hot Aisle
TensorWave
- AMD Instinct Accelerators
Powered by AMD Instinctโข 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
Hot Aisle
Advantages
Considerations
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
Hot Aisle
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
Hot Aisle
TensorWave
Getting Started
Hot Aisle
TensorWave
- 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
Hot Aisle
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.
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