Compare NVIDIA DGX Cloud with top alternatives in the cloud infrastructure category. Find detailed side-by-side comparisons to help you choose the best tool for your needs.
These tools are commonly compared with NVIDIA DGX Cloud and offer similar functionality.
Machine Learning Platform
Amazon's comprehensive machine learning platform that serves as the center for data, analytics, and AI workloads on AWS.
AI Platform
Google Cloud's unified platform for machine learning and generative AI, offering 180+ foundation models, custom training, and enterprise MLOps tools.
Infrastructure
Cloud infrastructure platform providing GPU-accelerated compute services specifically designed for AI and machine learning workloads.
Other tools in the cloud infrastructure category that you might want to compare with NVIDIA DGX Cloud.
Cloud Infrastructure
Emerging ecosystem of platforms where businesses discover, purchase, and deploy pre-built AI agents, including ServiceNow Store, Microsoft Marketplace, and AI Agent Store directories.
Cloud Infrastructure
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Cloud Infrastructure
Serverless PostgreSQL with instant branching, autoscaling from zero, and usage-based pricing for modern applications.
Cloud Infrastructure
Serverless MySQL database platform with database branching capabilities that enables development teams to manage schema changes like code. PlanetScale provides automatic scaling, horizontal sharding, and non-blocking schema changes, making it ideal for applications requiring high-performance MySQL with modern development workflows and zero-downtime deployments.
Cloud Infrastructure
Revolutionary Infrastructure-as-code orchestration platform that manages Terraform, OpenTofu, Pulumi, Ansible, and CloudFormation workflows with policy-as-code, drift detection, and concurrency-based pricing that won't surprise you.
Cloud Infrastructure
Open-source Firebase alternative built on PostgreSQL providing database, authentication, real-time subscriptions, edge functions, storage, and vector search â with auto-generated REST and GraphQL APIs.
đĄ Pro tip: Most tools offer free trials or free tiers. Test 2-3 options side-by-side to see which fits your workflow best.
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.
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.
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 â 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.
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.
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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