
NVIDIA DGX Cloud
6.2/10A managed AI training and inference platform on NVIDIA GPU clusters hosted with major clouds and NVIDIA Cloud Partners. It is aimed at enterprises and AI developers.
Data last updated November 2026 · Our methodology
Overview
NVIDIA DGX Cloud is NVIDIA's managed GPU platform for building and running AI at scale. NVIDIA describes it as a fully managed AI training platform. It runs on GPU clusters that NVIDIA co-engineers with AWS, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure, and customers get access to NVIDIA experts. NVIDIA also uses it to build its own models, such as Nemotron, and its physical AI work such as Cosmos and Isaac GR00T. Alongside it sits DGX Cloud Lepton, launched in May 2025 after NVIDIA bought Lepton AI. Lepton is a marketplace that routes developers to GPU capacity from partners such as Lambda, CoreWeave, Crusoe and Nebius, and it has since added AWS and Azure. Its documentation covers dev pods, endpoints, batch jobs, storage, region selection, a CLI and an API. Prebuilt NIM microservices and serverless endpoints are offered through build.nvidia.com. NVIDIA does not publish prices for DGX Cloud. You request a private offer through a cloud marketplace, with flexible term lengths, and the Google Cloud, Azure and Oracle listings advertise free trials. On Lepton, each partner sets and bills its own rate. A July 2026 third-party survey put H100 rates at roughly $3.85 to $12.29 per GPU-hour, depending on the provider. The product suits enterprises and well-funded AI teams that need large multi-node GPU clusters with NVIDIA's software stack and support. It is not a general web hosting service. Its main limitation is that pricing is opaque and negotiated. Press reports say NVIDIA has scaled back DGX Cloud as a direct rival to the hyperscalers in favor of the Lepton marketplace model, which raises questions about the product's long-term direction.
Our Rating
Hosting & Infrastructure6.5/10
AI Software5.9/10
Who NVIDIA DGX Cloud is best for
Good fit
It is sold through private offers with flexible terms and access to NVIDIA experts, for large-scale AI training.
Lepton gives AI developers dev pods, endpoints, batch jobs, a CLI and an API, though access requires an application.
Less suited
Lepton partner rates on per-GPU-hour pricing are accessible, but core DGX Cloud requires negotiated private offers.
Pros & Cons
Pros
- Clusters are co-engineered with each major cloud (AWS, Google Cloud, Azure, OCI) and come with NVIDIA's full software stack.
- Customers get access to NVIDIA experts, which is rare among GPU cloud providers.
- Lepton gives a single workflow across many GPU providers, with region choice for data sovereignty.
- Through build.nvidia.com, developers can use prebuilt NIM microservices and serverless endpoints without managing clusters.
Cons
- NVIDIA publishes no prices, and the core service requires a negotiated private offer.
- Review-site summaries repeatedly describe the pricing as expensive.
- Press reports say NVIDIA has scaled back DGX Cloud as a hyperscaler rival, so its direction is uncertain.
- Lepton access requires an application, and NVIDIA controls the allocation layer between you and the partner providers.
Key Features
NVIDIA DGX Cloud Pricing
DGX Cloud Lepton (partner-priced)
- Region selection
- Dev pods, endpoints and batch jobs
- Each partner provider sets and bills its own GPU rate
DGX Cloud private offer
- Flexible term lengths
- Access to NVIDIA experts
- Private offers via AWS, Google Cloud, Azure and OCI marketplaces
- Free trial listed on the Google Cloud, Azure and Oracle marketplaces
Frequently Asked Questions
NVIDIA does not publish a price list. You request a private offer through the AWS, Google Cloud, Azure or OCI marketplace. On DGX Cloud Lepton, each partner sets its own GPU-hour rate.
Yes. NVIDIA's DGX Cloud page lists free trials on the Google Cloud, Azure and Oracle marketplaces.
It is a marketplace NVIDIA launched in May 2025 after buying Lepton AI. It connects developers to GPU capacity from partners such as Lambda, CoreWeave, Crusoe and Nebius, and from AWS and Azure. Partners bill users directly.
Yes. Lepton lets you pick compute in specific regions to meet data sovereignty and latency needs, though NVIDIA does not publish a full list of regions.
Yes. The Lepton documentation covers both a CLI and an API, alongside dev pods, endpoints, batch jobs and storage.
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