Top 5 Platforms to Build AI Applications With NVIDIA NIM

Here’s a look at the top five platforms that have embedded NIM into their tool stack.

NVIDIA NIM helps simplify the challenges of building AI applications with industry-standard APIs and libraries in popular large language model (LLM) development frameworks, making integrating AI models into your application easy.

Here’s a look at the top five platforms that have embedded NIM into their tool stack.

1. Saturn Cloud

Saturn Cloud is a platform for data scientists and ML engineers who need a powerful, scalable, and easy-to-use cloud infrastructure. With NVIDIA NIM integrated, users can leverage NVIDIA’s AI capabilities without complex setups and utilize them across their preferred cloud solutions (AWS, Azure, Coreweave, etc). Key highlights include:

  • Multi-Cloud: Runs on any cloud, including AWS, Azure, GCP, and more

  • High Performance: Access to NVIDIA GPUs ensures rapid processing and analysis.

  • Ease of Use: User-friendly interface simplifies deployment and management of AI projects.

  • Collaboration: Teams can collaborate and easily share work by creating groups.

  • Scalability: Seamless scaling from individual projects to enterprise-level applications.

  • Fast Support: Excellent customer service to help you make the most of NVIDIA’s tools.

✅   Best For:  

Data scientists and bioinformatics researchers seeking a streamlined and efficient cloud platform for their AI projects.

🛠️   Setup Complexity:  

Low, minimal effort required.

Deploy generative AI on saturn cloud using NVIDIA NIM

2. AWS (Amazon Web Services) SageMaker

AWS provides infrastructure and a vast array of services, including embedding NVIDIA’s AI tools into their offerings. Highlights include:

  • Global Infrastructure: Extensive network of data centers ensures low latency and high availability.

  • Flexibility: Wide range of instance types, including those optimized for GPU workloads.

  • Integration: Seamless integration with other AWS services for a holistic cloud experience.

  • AWS-Only: Works only within the AWS ecosystem, excluding other clouds such as Azure, OCI, GCP, etc.

✅   Best For:  

Organizations needing global reach and flexibility in their bioinformatics and AI projects.

🛠️   Setup Complexity:  

Moderate, some setup and management required.

3. Vertex AI

Vertex AI offers an environment for developing and deploying AI models. With the integration of NVIDIA NIM, users can now access its capabilities for AI applications. Highlights include:

  • Advanced AI Tools: Access Google’s AI and ML services alongside NVIDIA’s tools.

  • Scalable Infrastructure: Designed to handle workloads of any size, from small research projects to large-scale deployments.

  • Collaboration: Tools like Google Colab and AI Hub facilitate team collaboration and sharing of models and data.

  • Vertex-Only: Works only within Vertex/Google ecosystem, excluding other clouds such as AWS, OCI, Azure, etc.

✅   Best For:  

Teams looking for an integrated environment that supports collaboration and scalability.

🛠️   Setup Complexity:  

Low, user-friendly tools and services reduce the need for extensive setup.

4. Microsoft Azure ML Studio

Azure’s cloud platform supports NVIDIA’s latest AI tools for building AI applications and more. Azure’s key highlights include:

  • Enterprise Integration: Integration with existing Microsoft products like Office 365 and Azure DevOps.

  • Security: Security features and compliance certifications suitable for sensitive healthcare data.

  • Performance: High-performance computing capabilities with NVIDIA GPUs for intensive AI tasks.

  • Azure-Only: Works only within Azure ecosystem, excluding other clouds such as AWS, OCI, etc.

✅   Best For:  

Enterprises needing secure, high-performance cloud solutions with smooth Microsoft ecosystem integration.

🛠️   Setup Complexity:  

Moderate, some setup and management required but streamlined with Microsoft’s tools.

5. Oracle Cloud

Oracle Cloud offers an environment optimized for enterprise workloads, including those involving NVIDIA NIM. Key benefits include:

  • Enterprise Optimization: Designed to handle large-scale enterprise applications with ease.

  • High Performance: Access to NVIDIA GPUs for accelerated AI and ML workloads.

  • Security and Compliance: Offers security features and compliance certifications suitable for sensitive data.

  • Oracle-Only: Works only within Oracle ecosystem, excluding other clouds such as AWS, Azure, Google, etc.

✅   Best For:  

Large enterprises requiring high-performance computing and secure, compliant cloud solutions.

🛠️   Setup Complexity:  

Moderate, some setup and management required, but well-supported by Oracle’s tools.

Other MLOps Platforms

Other AI and MLOps platforms including Amazon SageMaker, Dataiku, DataRobot, deepset, Domino Data Lab, LangChain, Llama Index, Replicate, Run.ai, and more have also embedded NIM into their platforms, however, may require additional DevOps support and configuration.

Choosing the Right Platform

Choosing the right platform to run NVIDIA NIM can significantly impact the success of your AI projects. Saturn Cloud stands out for its user-friendly interface, scalability, and excellent support, making it a top choice for many researchers. However, platforms like AWS, Google Cloud, Microsoft Azure, and OCI offer unique advantages, depending on your needs and existing infrastructure. Evaluate these options to find the best fit for your AI-driven research.

NVIDIA NIM Microsrvices

(NVIDIA NIM is a containerized inference microservice including industry-standard APIs, domain-specific code, optimized inference engines, and enterprise runtime. Source.)

By leveraging these platforms, enterprise teams can shorten their time-to-market and simplify the deployment of generative AI models anywhere. Whether you prioritize ease of use, global reach, or dedicated AI infrastructure, there’s a platform tailored to your needs.

Learn more about NVIDIA NIM for developers here or NIM’s inference microservices here.


About Saturn Cloud

Saturn Cloud is your all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, and more. Request a demo today to learn more.