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Cloud Infrastructure
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NVIDIA DGX Cloud

NVIDIA's cloud platform providing access to powerful GPU infrastructure for AI model training, inference, and high-performance computing workloads.

Starting at~$36,999/month per instance
Visit NVIDIA DGX Cloud →
OverviewFeaturesPricingUse CasesLimitationsFAQSecurityAlternatives

Overview

NVIDIA DGX Cloud is a Cloud Infrastructure platform that delivers dedicated access to NVIDIA's latest GPU supercomputing architecture for training, fine-tuning, and deploying generative AI models, with pricing available through enterprise agreements starting at approximately $36,999 per instance per month. It is designed for large enterprises, AI research labs, and organizations building foundation models who require turnkey access to thousands of interconnected GPUs without building their own data centers.

DGX Cloud is co-engineered with leading cloud service providers including Oracle Cloud Infrastructure, Microsoft Azure, Google Cloud, and AWS, giving customers a consistent NVIDIA software stack across hyperscalers. Each DGX Cloud instance provides access to eight NVIDIA H100 or A100 80GB Tensor Core GPUs (640GB of total GPU memory per node), high-speed NVLink and InfiniBand interconnects for multi-node scaling, and NVIDIA AI Enterprise software including NeMo, RAPIDS, and pre-trained foundation models. The platform is optimized for training trillion-parameter large language models, computer vision workloads, and recommender systems that would otherwise require months of infrastructure procurement.

Compared to the other cloud infrastructure tools in our directory — such as AWS SageMaker, Google Vertex AI, CoreWeave, and Lambda Labs — DGX Cloud differentiates by offering reserved, serverless-style access to full NVIDIA reference architectures (not shared multi-tenant GPUs), direct access to NVIDIA's engineering and AI expert concierge, and integration with NVIDIA Base Command for job orchestration. Based on our analysis of 870+ AI tools, DGX Cloud sits at the premium tier of GPU cloud infrastructure: it is not designed for hobbyists or solo developers, but rather for Fortune 500 enterprises, sovereign AI initiatives, and well-funded AI startups training frontier models. NVIDIA announced DGX Cloud in March 2023 and has since expanded it with DGX Cloud Lepton (GPU marketplace), DGX Cloud Serverless Inference, and DGX Cloud Benchmarking introduced throughout 2024 and 2025.

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Key Features

Dedicated NVIDIA Reference Architecture+

Each DGX Cloud instance is a full 8-GPU node built to NVIDIA's DGX H100 or A100 reference design, with 640GB of total GPU memory, NVLink intra-node interconnect, and NVIDIA Quantum-2 400 Gb/s InfiniBand between nodes. This is the same hardware NVIDIA uses to train its own foundation models, ensuring predictable performance at scale.

NVIDIA AI Enterprise Software Suite+

DGX Cloud bundles the full NVIDIA AI Enterprise stack, including NeMo for large language model development, RAPIDS for GPU-accelerated data science, and Triton Inference Server. This software is otherwise licensed at approximately $4,500 per GPU per year, so the bundle represents meaningful value for multi-GPU deployments.

Base Command Platform Orchestration+

NVIDIA Base Command provides a managed interface for scheduling, monitoring, and managing multi-node training jobs on DGX Cloud. It handles cluster health, data movement, and experiment tracking, reducing the DevOps burden compared to rolling your own Kubernetes or Slurm cluster on raw cloud GPUs.

DGX Cloud Lepton Marketplace+

Launched in 2025, DGX Cloud Lepton is a unified GPU marketplace that aggregates capacity from NVIDIA's partner clouds like CoreWeave, Lambda, and Nebius. Developers can provision GPUs across providers through a single API, improving availability during GPU shortages and enabling geographic flexibility for data residency.

Direct Access to NVIDIA AI Experts+

DGX Cloud customers receive concierge-level support from NVIDIA's AI engineers, who have hands-on experience training the company's own foundation models. This includes architecture review, performance tuning, and guidance on NeMo workflows — a service that would cost hundreds of thousands of dollars if procured from a third-party ML consultancy.

Pricing Plans

Enterprise Reserved Instance

~$36,999/month per instance

  • ✓Dedicated 8x NVIDIA H100 or A100 80GB GPU node (640GB total GPU memory)
  • ✓NVLink intra-node and InfiniBand inter-node interconnects
  • ✓NVIDIA AI Enterprise software suite included (NeMo, RAPIDS, Triton)
  • ✓NVIDIA Base Command job orchestration platform
  • ✓Direct access to NVIDIA AI expert concierge support
  • ✓Deployable across Azure, OCI, Google Cloud, and AWS
  • ✓Reserved, non-preemptible capacity
  • ✓Monthly or annual commitment terms negotiated via enterprise sales
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Best Use Cases

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Training foundation large language models with 70B+ parameters where multi-node InfiniBand scaling is required, such as building domain-specific LLMs for finance, legal, or healthcare

⚡

Sovereign AI initiatives where governments or national labs need dedicated, isolated GPU capacity with NVIDIA reference architecture to train models on regulated data

🔧

Enterprise fine-tuning of Llama, Mixtral, or proprietary models using NVIDIA NeMo where teams need integrated data curation, model customization, and evaluation workflows

🚀

Recommender system training at hyperscale (e.g., retail, ads, media) where terabyte-scale embedding tables require high GPU memory and fast interconnect

💡

Drug discovery and molecular simulation workloads using NVIDIA BioNeMo on dedicated H100 nodes, particularly for pharma companies running protein structure prediction

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Multi-cloud AI strategies where a Fortune 500 enterprise wants a consistent NVIDIA stack deployable across Azure, OCI, Google Cloud, and AWS to negotiate vendor leverage

Limitations & What It Can't Do

We believe in transparent reviews. Here's what NVIDIA DGX Cloud doesn't handle well:

  • ⚠No hourly or on-demand billing — customers commit to monthly or annual reserved terms, unlike Lambda Labs, RunPod, or Vast.ai
  • ⚠Not available as self-serve; requires engaging NVIDIA or a cloud partner's enterprise sales team to onboard
  • ⚠Tightly coupled to NVIDIA's CUDA and AI Enterprise stack; not suitable for teams standardized on AMD ROCm, Google TPUs, or AWS Trainium
  • ⚠Geographic region availability is narrower than general-purpose cloud GPU services, with concentration in North America and Europe
  • ⚠Pricing opacity — list prices are not published on the NVIDIA DGX Cloud page and vary by cloud partner and negotiation

Pros & Cons

✓ Pros

  • ✓Provides turnkey access to 8x NVIDIA H100 80GB GPUs per node (640GB total GPU memory) without capital expenditure on hardware
  • ✓Includes white-glove support from NVIDIA AI experts who have trained foundation models at scale
  • ✓Bundles NVIDIA AI Enterprise software (NeMo, RAPIDS, Triton) valued at $4,500 per GPU per year at no additional charge
  • ✓Runs on identical NVIDIA reference architecture across Azure, OCI, Google Cloud, and AWS — avoiding cloud vendor lock-in
  • ✓Reserved capacity eliminates the 'GPU scarcity' problem that plagues on-demand instances at other hyperscalers
  • ✓Optimized high-speed InfiniBand interconnects enable efficient scaling to thousands of GPUs for trillion-parameter models

✗ Cons

  • ✗Starting price of approximately $36,999 per instance per month makes it inaccessible to solo developers and small startups
  • ✗Requires multi-month commitments, not hourly or on-demand billing like Lambda Labs or Vast.ai
  • ✗Sales process is enterprise-driven and can take weeks to onboard, unlike self-service cloud GPU providers
  • ✗Limited geographic availability compared to mature hyperscaler regions
  • ✗Locked into NVIDIA's software ecosystem (CUDA, NeMo) — less friendly to AMD ROCm or custom silicon workflows

Frequently Asked Questions

How much does NVIDIA DGX Cloud cost?+

NVIDIA DGX Cloud pricing starts at approximately $36,999 per instance per month for an 8-GPU node with H100 or A100 GPUs, based on initial Microsoft Azure listings. Pricing is sold on reserved terms (typically monthly or annual) rather than hourly on-demand billing. All plans include NVIDIA AI Enterprise software, Base Command orchestration, and direct access to NVIDIA AI experts. Actual pricing varies by cloud partner (OCI, Azure, Google Cloud, AWS), GPU generation, and term length, and is negotiated through NVIDIA or the cloud provider's enterprise sales team.

What GPUs does DGX Cloud provide access to?+

DGX Cloud provides dedicated access to NVIDIA's flagship data center GPUs, including the H100 Tensor Core GPU (80GB HBM3) and A100 80GB. Each DGX Cloud node includes 8 GPUs connected by NVLink for 640GB of total GPU memory and multi-node configurations are connected by NVIDIA Quantum-2 InfiniBand at 400 Gb/s. NVIDIA has also announced Blackwell-based GB200 and GB300 NVL72 rack-scale systems coming to DGX Cloud, which will further accelerate trillion-parameter model training. Unlike shared cloud GPU offerings, DGX Cloud nodes are reserved, not preemptible.

How does DGX Cloud compare to AWS SageMaker or Google Vertex AI?+

DGX Cloud is infrastructure-first and optimized for training foundation models, while AWS SageMaker and Google Vertex AI are end-to-end ML platforms with broader tooling for deployment, feature stores, and AutoML. DGX Cloud delivers higher raw GPU performance per dollar for large-scale training because it uses NVIDIA reference architecture with dedicated InfiniBand fabric — not virtualized multi-tenant GPUs. Based on our analysis of 870+ AI tools, teams training models over 70B parameters typically choose DGX Cloud, while teams focused on managed ML pipelines and inference at variable scale choose SageMaker or Vertex. DGX Cloud also runs inside Azure, Google Cloud, OCI, and AWS, so customers can retain existing cloud billing relationships.

Can I try DGX Cloud before committing to a contract?+

NVIDIA does not offer a self-service free trial for DGX Cloud in the traditional sense, but enterprise prospects can request a proof-of-concept engagement through NVIDIA's sales team. Developers who want to experiment with the same NVIDIA AI Enterprise software stack can use NVIDIA LaunchPad, which provides short-term free access to curated labs on DGX-class hardware. The NVIDIA NGC catalog also offers free access to pre-trained models and containers that run on DGX Cloud. For production workloads, expect a formal procurement process rather than a credit card checkout.

What is the difference between DGX Cloud and DGX Cloud Lepton?+

DGX Cloud is the core reserved-capacity service offering dedicated H100/A100 multi-node instances with NVIDIA AI Enterprise software. DGX Cloud Lepton, announced in 2025, is a GPU marketplace that aggregates compute capacity from a global network of NVIDIA cloud partners (GPU clouds like CoreWeave, Lambda, Nebius, and others), giving developers a unified API to access GPUs across providers. Lepton is designed for developers who want flexibility and broader GPU availability, while DGX Cloud proper is for enterprises committing to dedicated infrastructure. NVIDIA also offers DGX Cloud Serverless Inference for pay-per-call model deployment built on top of the same infrastructure.
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What's New in 2026

In 2025 NVIDIA expanded DGX Cloud with three major additions: DGX Cloud Lepton, a unified GPU marketplace aggregating capacity across NVIDIA cloud partners like CoreWeave, Lambda, and Nebius; DGX Cloud Serverless Inference for pay-per-call model deployment; and DGX Cloud Benchmarking for standardized performance evaluation. NVIDIA has also announced Blackwell-based GB200 and GB300 NVL72 rack-scale systems coming to DGX Cloud, further accelerating trillion-parameter training workloads into 2026.

Alternatives to NVIDIA DGX Cloud

AWS SageMaker

Machine Learning Platform

Amazon's comprehensive machine learning platform that serves as the center for data, analytics, and AI workloads on AWS.

Google Vertex AI

AI Platform

Google Cloud's unified platform for machine learning and generative AI, offering 180+ foundation models, custom training, and enterprise MLOps tools.

CoreWeave

Infrastructure

Cloud infrastructure platform providing GPU-accelerated compute services specifically designed for AI and machine learning workloads.

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Quick Info

Category

Cloud Infrastructure

Website

www.nvidia.com/en-us/data-center/dgx-cloud/
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