TensorWave
AMD-powered cloud challenging Nvidia dominance
TensorWave is an AMD‑first AI cloud with bare‑metal and managed clusters built on Instinct MI300X/MI325X/MI355X accelerators with large VRAM and ROCm.
Available GPUs
Hourly on-demand pricing. Click column headers to sort.
Prices last updated: April 7, 2026
Pros & Cons
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
- Utilizes an open-source software stack (ROCm)
- Offers bare metal access for greater control
Limitations
- 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
- A smaller ecosystem when compared to major cloud providers
Key Features
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.
Compute Services
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
Availability & Support
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.
Getting 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.
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