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Description
Lambda is a cloud GPU platform built exclusively for AI workloads. Founded in 2012 by ML engineers, the company provides on-demand GPU instances, production-ready clusters, and large-scale supercomputer infrastructure to power every stage of the AI development lifecycle — from rapid prototyping to foundation model training and global-scale inference.
The platform offers three core products: Instances, 1-Click Clusters, and Superclusters. Instances let teams spin up NVIDIA B200, H100, A100, or GH200 GPUs in minutes with pay-by-the-minute billing and no egress fees. 1-Click Clusters provide production-ready NVIDIA HGX B200 and H100 GPU clusters from 16 to over 2,000 GPUs, fully optimized for distributed AI workloads. Superclusters are single-tenant NVIDIA GB300 NVL72 systems connected via NVIDIA Quantum-2 InfiniBand, designed for maximum performance, security, and scale.
Lambda Stack comes pre-installed with essential ML tools including PyTorch and CUDA, enabling teams to begin training or inference immediately without driver installs or environment setup. Built-in observability provides live, minute-by-minute visibility into GPU, memory, and network performance directly from the dashboard or API.
Security and compliance are central to the platform. Lambda operates under a single-tenant, shared-nothing architecture and holds SOC 2 Type II certification. Caged clusters with hardware-level isolation ensure data protection for enterprises and government organizations handling sensitive workloads. Lambda Cloud API support enables automation via CLI, CI/CD pipelines, and orchestration scripts.
Use cases
- Training large-scale foundation models on single-tenant NVIDIA GPU supercomputers
- Fine-tuning open-source language models using on-demand H100 or B200 instances
- Serving inference at global scale across billions of tokens with dedicated compute
- Prototyping and testing AI models by spinning up instances in minutes with no lengthy setup
- Running distributed AI workloads across 16 to 2000 or more interconnected GPU clusters
- Deploying AI in regulated industries with SOC 2 Type II compliant single-tenant infrastructure
- Automating GPU lifecycle management via Lambda Cloud API from CLI or CI/CD pipelines
- Scaling research computing from a single GPU to hundreds of thousands for frontier AI labs
- Supporting government AI programs with dedicated secure compute and hardware-level isolation
- Benchmarking GPU performance using the built-in real-time observability dashboard
