What types of GPUs does Lambda Labs offer?

Lambda Labs primarily offers NVIDIA's leading-edge GPUs, including the H100, A100, and V100, alongside other options, focusing on high-performance computing for AI.

How does Lambda Labs' pricing compare to AWS or GCP?

Lambda Labs typically offers significantly more competitive pricing for raw GPU compute power compared to major public cloud providers like AWS, GCP, or Azure, especially for long-running or large-scale ML workloads.

Can I use my custom Docker images for my ML projects?

Yes, Lambda Labs fully supports custom Docker images, allowing users to bring their own environments and dependencies directly to their GPU instances.

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Lambda Labs

Paid

aigpu

Lambda Labs provides on-demand, high-performance GPU cloud infrastructure specifically designed for machine learning and deep learning workloads.

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GPU cloud for ML.

Lambda Labs offers cloud-based GPUs, bare metal servers, and GPU workstations tailored for AI development, research, and deployment. Their infrastructure is built to deliver raw computing power, reducing training times and accelerating model development for data scientists and engineers. They differentiate themselves through competitive pricing, a focus on cutting-edge GPU hardware (e.g., NVIDIA H100s, A100s), and a user-friendly platform that prioritizes ease of access and deployment for complex ML tasks. The service allows users to provision instances with various GPU configurations and pre-configured deep learning environments.

Pros

Access to the latest and most powerful NVIDIA GPUs (H100, A100) often before other providers.
Highly competitive pricing for GPU compute compared to major cloud providers.
Simplified setup and pre-configured environments for common deep learning frameworks.

Cons

Smaller ecosystem and fewer integrated services compared to hyperscale cloud providers for non-ML tasks.
Customer support might be less extensive or slower than larger, more established cloud platforms.
Availability of the newest, most requested GPUs can sometimes be limited due to high demand.

Key features

On-demand GPU instances (H100, A100, V100)
Bare metal GPU servers for maximum performance
Pre-configured deep learning environments (TensorFlow, PyTorch, etc.)
High-speed interconnects (NVLink, InfiniBand)
API and CLI for programmatic control

Integrations

Docker/nvidia-container-toolkitPyTorchTensorFlowJupyter NotebooksSSHGit

Target audience

Data scientists, machine learning engineers, AI researchers, and startups requiring high-performance GPU infrastructure for training and deploying deep learning models.

Ratings & Reviews

0.0

Based on 0 reviews

Key Metrics

Active Users

10K+

Founded

2012

Headquarters

San Jose, California/USA

Pricing Tiers

On-Demand GPU Instances

Hourly billing for various GPU configurations (e.g., A100 80GB, V100 32GB).

Starts from $1.15/hour (e.g., V100)

Bare Metal Servers

Monthly or annual leases for dedicated GPU servers (e.g., 8x A100).

Starts from $4,995/month

GPU Workstations

Purchase high-end GPU workstations for on-premise development.

Custom

Frequently Asked Questions

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