
The superintelligence cloud for GPU compute and AI infrastructure
Lambda is a GPU cloud platform purpose-built for AI training and inference at scale. Founded in 2012 by ML engineers, it provides on-demand and reserved GPU instances, 1-Click Clusters, and single-tenant superclusters powered by NVIDIA B200, H100, and A100 GPUs across 15+ global data centers.
Pre-optimized multi-node NVIDIA HGX B200 and H100 clusters that scale from 16 to 2,000+ GPUs for distributed training workloads
On-demand single and multi-GPU instances with B200, H100, GH200, A100, and A6000 options for rapid prototyping and smaller jobs
Single-tenant NVIDIA GB300 NVL72 clusters with dedicated power, cooling, and physical isolation for frontier AI training
No charges for data transfer out, saving thousands compared to AWS and other hyperscalers on large dataset workflows
High-speed InfiniBand interconnect included as standard for low-latency multi-node distributed training
Enterprise-grade security with single-tenant, shared-nothing architecture and optional caged-cluster deployments
One-liner installation of PyTorch, TensorFlow, and other ML frameworks with SSH and JupyterLab access out of the box
Train frontier LLMs on 1-Click Clusters with hundreds of H100 or B200 GPUs connected via InfiniBand at a fraction of hyperscaler costs
Spin up on-demand GPU instances for rapid prototyping, paper reproduction, and model experiments without long-term commitments
Train and fine-tune image generation, object detection, and video models on A100 or H100 instances with pre-configured PyTorch
Deploy single-tenant superclusters with SOC 2 compliance for regulated industries requiring physical isolation and security
Real-time GPU utilization monitoring and workload metrics without needing to set up external observability tools
Fine-tune Llama, Mistral, and other open-source models on cost-effective A100 or H100 instances starting at $1.29/hr

The end-to-end GPU cloud for AI workloads