Lambda Labs vs TensorWave
Compare GPU pricing, features, and specifications between Lambda Labs and TensorWave cloud providers. Find the best deals for AI training, inference, and ML workloads.
Lambda Labs
Provider 1
TensorWave
Provider 2
Comparison Overview
GPU Pricing Comparison
| GPU Model ↑ | Lambda Labs Price | TensorWave Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A10 24GB VRAM • Lambda Labs | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 PCIE 40GB VRAM • Lambda Labs | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Lambda Labs | 8x GPU | Not Available | — | |
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • Lambda Labs | Not Available | — | ||
B200 192GB VRAM • | ||||
GH200 96GB VRAM • Lambda Labs | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 80GB VRAM • Lambda Labs | Not Available | — | ||
H100 80GB 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 • | ||||
RTX 6000 Ada 48GB VRAM • Lambda Labs | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX 6000 Pro 96GB VRAM • Lambda Labs | Not Available | — | ||
RTX 6000 Pro 96GB VRAM • | ||||
RTX A6000 48GB VRAM • Lambda Labs | 4x GPU | Not Available | — | |
RTX A6000 48GB VRAM • | ||||
Tesla V100 32GB VRAM • Lambda Labs | 8x GPU | Not Available | — | |
Tesla V100 32GB VRAM • | ||||
A10 24GB VRAM • Lambda Labs | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 PCIE 40GB VRAM • Lambda Labs | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Lambda Labs | 8x GPU | Not Available | — | |
A100 SXM 80GB VRAM • | ||||
B200 192GB VRAM • Lambda Labs | Not Available | — | ||
B200 192GB VRAM • | ||||
GH200 96GB VRAM • Lambda Labs | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 80GB VRAM • Lambda Labs | Not Available | — | ||
H100 80GB 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 • | ||||
RTX 6000 Ada 48GB VRAM • Lambda Labs | Not Available | — | ||
RTX 6000 Ada 48GB VRAM • | ||||
RTX 6000 Pro 96GB VRAM • Lambda Labs | Not Available | — | ||
RTX 6000 Pro 96GB VRAM • | ||||
RTX A6000 48GB VRAM • Lambda Labs | 4x GPU | Not Available | — | |
RTX A6000 48GB VRAM • | ||||
Tesla V100 32GB VRAM • Lambda Labs | 8x GPU | Not Available | — | |
Tesla V100 32GB VRAM • | ||||
Features Comparison
Lambda Labs
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
Lambda Labs
Advantages
- Early access to latest NVIDIA GPUs (H100, H200, Blackwell)
- Specialized for AI workloads
- One-click Jupyter access
- Pre-installed popular ML frameworks
Considerations
- Primarily focused on AI and ML workloads
- Limited global data center presence compared to major cloud providers
- Newer player in the cloud GPU market
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
Lambda Labs
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
Lambda Labs
TensorWave
Getting Started
Lambda Labs
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
Lambda Labs
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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