# Lambda

> Lambda (lambda.ai) is "The Superintelligence Cloud" — a GPU cloud and AI infrastructure company providing NVIDIA-accelerated compute for training and inference at every scale, from a single on-demand GPU instance to dedicated, single-tenant superclusters with thousands of GPUs.

Notes for interpreting this site:

- "Lambda" here refers to the GPU cloud provider at lambda.ai (formerly branded "Lambda Labs" / "Lambda Cloud"). It is NOT AWS Lambda, the serverless-functions product from Amazon Web Services; the two are unrelated companies and products.
- Lambda's compute spans NVIDIA Rubin-generation systems (VR200 NVL72), Blackwell-generation systems (GB300 NVL72, HGX B300, HGX B200) and Hopper-generation GPUs (H200, H100).
- Cloud products scale across three tiers: on-demand single-node Instances; self-serve multi-node 1-Click Clusters; and Superclusters — Lambda's single-tenant Private Cloud for dedicated, large-scale deployments (4,000+ GPUs). "Superclusters" (the product name) and "Private Cloud" (the deployment/documentation name) refer to the same single-tenant offering.
- Infrastructure is single-tenant and shared-nothing, with SOC 2 Type II attestation and ISO 27001, ISO 27017, ISO 27701, and ISO 22301 certifications.
- Fast-changing details — GPU pricing and region/GPU availability — live on the linked Pricing and Documentation pages rather than in this file.

## Products

- Cloud overview and compare: Side-by-side comparison of Lambda's cloud compute options.
- Instances: On-demand, single-node NVIDIA HGX B200 and H100 instances launchable in minutes for prototyping, fine-tuning, and inference. Also the starting point for startups and researchers.
- 1-Click Clusters: Production-ready, self-serve multi-node NVIDIA HGX B200 and H100 GPU clusters optimized for distributed AI workloads.
- Superclusters (single-tenant Private Cloud): Dedicated, single-tenant NVIDIA VR200 NVL72 and GB300 NVL72 clusters with NVIDIA Quantum-2 InfiniBand for large-scale training and inference (4,000+ GPUs). This is Lambda's Private Cloud offering.
- Pricing: Current GPU cloud pricing.

## Solutions by mission

- Superintelligence: Frontier-scale training and inference for labs building the world's most advanced models.
- Enterprise: Secure, compliant GPU infrastructure for production AI workloads.
- Government: Compute for public-sector and mission-critical deployments.
- Startups and researchers: On-demand instances for smaller teams getting started.

## Platform and infrastructure

- AI factories / AI infrastructure: End-to-end AI factories integrating high-density power, liquid cooling, and NVIDIA GPUs into one system.
- Orchestration: Managed cluster orchestration (Managed Kubernetes, Slurm) so teams can run large-scale workloads without the operational burden.
- Lambda Stack: One-line install and management of CUDA, cuDNN, PyTorch, TensorFlow, and NVIDIA drivers across Lambda systems.
- Trust and security: Security architecture, compliance posture, and certifications.
- Trust Portal: Live compliance documentation and attestations (SOC 2 Type II; ISO 27001/27017/27701/22301).

## Documentation

- Documentation home: Lambda GPU Cloud documentation.
- Public Cloud: Launching single-node instances and 16x–512x H100/B200 clusters, with Managed Kubernetes, Preinstalled Kubernetes, or Slurm.
- Private Cloud: Documentation for Superclusters / Private Cloud — single-tenant clusters of 1,000+ GPUs with low-level access to cluster infrastructure.
- Managed Kubernetes: Running workloads on Lambda's managed Kubernetes.
- Education: guides and tutorials: ML-engineering guides, including model fine-tuning and self-hosting models for inference.

## Company

- About: Company overview and mission.
- Leadership: Executive team.
- Careers: Open roles at Lambda.
- Investors: Investor information.
- Partners: Partner and ecosystem program.

## Resources

- Blog: Product news, tutorials, and announcements.
- Research: Lambda research and technical publications.
- GPU benchmarks: Performance benchmarks across GPU types and workloads.
- Customer stories: Case studies from Lambda customers.
- Support: Help and support resources.

## Get started

- Create account / sign up: Sign up for an account, add a billing address and credit card (required for tax and fraud reasons, and launch a GPU instance.
- Talk to our team: Contact sales for clusters, private cloudm and enterprise needs.
- Log in: Existing-customer login and Cloud console.

## Optional

- Brand guidelines: Logo, color, and brand-usage guidance.
- Privacy Policy: Privacy policy.
- Terms of Service: Terms of service.
- LinkedIn: Company LinkedIn.
- X / Twitter: Company account on X.
- YouTube: Company YouTube channel.