The GPU Cloud for AI

On-demand & reserved cloud GPUs for AI training & inference

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RESERVED CLOUD
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Lambda Reserved Cloud powered by NVIDIA GH200

Lambda Reserved Cloud is now available with the NVIDIA GH200 Grace Hopper™ Superchip. A single GH200 has 576 GB of coherent memory for unmatched efficiency and price for the memory footprint.

PUBLIC CLOUD


The only public cloud designed for training LLMs & Generative AI


On-Demand Cloud

Spin up on-demand GPUs billed by the hour. NVIDIA H100 instances starting at $2.49/hr.


Reserved Cloud

Reserve thousands of NVIDIA H100s, H200s, and GH200s with Quantum-2 InfiniBand Networking.

NVIDIA H100 ON-DEMAND
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Starting at $2.49/GPU/Hour

NVIDIA H100s are now available on-demand

Lambda is one of the first cloud providers to make NVIDIA H100 Tensor Core GPUs available on-demand in a public cloud.

RESERVED CLOUD USE CASE

See how Voltron Data leverages Lambda Reserved Cloud

After completing an extensive evaluation on the cost-benefit analysis across all major cloud providers and various on-prem solutions, Voltron Data shares how the decision to partner with Lambda was based on the ability to deliver on availability and pricing in this compelling case study.

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NVIDIA DGX

NVIDIA DGX™ SuperPOD Clusters deployed by Lambda

 

NVIDIA DGX™ SuperPOD

Turnkey, full-stack, industry-leading infrastructure solution for the fastest path to AI innovation at scale.

 
 

Lambda's datacenter

Leverage Lambda’s datacenter for large scale GPU deployments. Pay a monthly fee for hosting and Lambda Support.
 
OPEN SOURCE
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Lambda Stack is used by more than 50k ML teams

One line installation and managed upgrade path for: PyTorch®, TensorFlow, CUDA, cuDNN, and NVIDIA Drivers. Learn more about Lambda Stack.

NVIDIA H200

NVIDIA H200 in Lambda Cloud

Lambda will be one of the first cloud providers in the world to offer customers access to NVIDIA H200 Tensor Core GPUs through Lambda Reserved Cloud. The H200, with 141GB of HBM3e memory, nearly doubles capacity over the prior-generation NVIDIA H100 GPU, for more efficient inference and training of massive LLMs.

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