Best AI Infrastructure Platforms for Jupyter Notebook

Compare the Top AI Infrastructure Platforms that integrate with Jupyter Notebook as of November 2025

This a list of AI Infrastructure platforms that integrate with Jupyter Notebook. Use the filters on the left to add additional filters for products that have integrations with Jupyter Notebook. View the products that work with Jupyter Notebook in the table below.

What are AI Infrastructure Platforms for Jupyter Notebook?

An AI infrastructure platform is a system that provides infrastructure, compute, tools, and components for the development, training, testing, deployment, and maintenance of artificial intelligence models and applications. It usually features automated model building pipelines, support for large data sets, integration with popular software development environments, tools for distributed training stacks, and the ability to access cloud APIs. By leveraging such an infrastructure platform, developers can easily create end-to-end solutions where data can be collected efficiently and models can be quickly trained in parallel on distributed hardware. The use of such platforms enables a fast development cycle that helps companies get their products to market quickly. Compare and read user reviews of the best AI Infrastructure platforms for Jupyter Notebook currently available using the table below. This list is updated regularly.

  • 1
    Azure Data Science Virtual Machines
    DSVMs are Azure Virtual Machine images, pre-installed, configured and tested with several popular tools that are commonly used for data analytics, machine learning and AI training. Consistent setup across team, promote sharing and collaboration, Azure scale and management, Near-Zero Setup, full cloud-based desktop for data science. Quick, Low friction startup for one to many classroom scenarios and online courses. Ability to run analytics on all Azure hardware configurations with vertical and horizontal scaling. Pay only for what you use, when you use it. Readily available GPU clusters with Deep Learning tools already pre-configured. Examples, templates and sample notebooks built or tested by Microsoft are provided on the VMs to enable easy onboarding to the various tools and capabilities such as Neural Networks (PYTorch, Tensorflow, etc.), Data Wrangling, R, Python, Julia, and SQL Server.
    Starting Price: $0.005
  • 2
    Intel Tiber AI Cloud
    Intel® Tiber™ AI Cloud is a powerful platform designed to scale AI workloads with advanced computing resources. It offers specialized AI processors, such as the Intel Gaudi AI Processor and Max Series GPUs, to accelerate model training, inference, and deployment. Optimized for enterprise-level AI use cases, this cloud solution enables developers to build and fine-tune models with support for popular libraries like PyTorch. With flexible deployment options, secure private cloud solutions, and expert support, Intel Tiber™ ensures seamless integration, fast deployment, and enhanced model performance.
    Starting Price: Free
  • 3
    Vertex AI Notebooks
    Vertex AI Notebooks is a fully managed, scalable solution from Google Cloud that accelerates machine learning (ML) development. It provides a seamless, interactive environment for data scientists and developers to explore data, prototype models, and collaborate in real-time. With integration into Google Cloud’s vast data and ML tools, Vertex AI Notebooks supports rapid prototyping, automated workflows, and deployment, making it easier to scale ML operations. The platform’s support for both Colab Enterprise and Vertex AI Workbench ensures a flexible and secure environment for diverse enterprise needs.
    Starting Price: $10 per GB
  • 4
    VESSL AI

    VESSL AI

    VESSL AI

    Build, train, and deploy models faster at scale with fully managed infrastructure, tools, and workflows. Deploy custom AI & LLMs on any infrastructure in seconds and scale inference with ease. Handle your most demanding tasks with batch job scheduling, only paying with per-second billing. Optimize costs with GPU usage, spot instances, and built-in automatic failover. Train with a single command with YAML, simplifying complex infrastructure setups. Automatically scale up workers during high traffic and scale down to zero during inactivity. Deploy cutting-edge models with persistent endpoints in a serverless environment, optimizing resource usage. Monitor system and inference metrics in real-time, including worker count, GPU utilization, latency, and throughput. Efficiently conduct A/B testing by splitting traffic among multiple models for evaluation.
    Starting Price: $100 + compute/month
  • 5
    NeevCloud

    NeevCloud

    NeevCloud

    NeevCloud delivers cutting-edge GPU cloud solutions powered by NVIDIA GPUs like the H200, H100, GB200 NVL72, and many more offering unmatched performance for AI, HPC, and data-intensive workloads. Scale dynamically with flexible pricing and energy-efficient GPUs that reduce costs while maximizing output. Ideal for AI model training, scientific research, media production, and real-time analytics, NeevCloud ensures seamless integration and global accessibility. Experience unparalleled speed, scalability, and sustainability with NeevCloud GPU cloud solutions.
    Starting Price: $1.69/GPU/hour
  • 6
    E2E Cloud

    E2E Cloud

    ​E2E Networks

    ​E2E Cloud provides advanced cloud solutions tailored for AI and machine learning workloads. We offer access to cutting-edge NVIDIA GPUs, including H200, H100, A100, L40S, and L4, enabling businesses to efficiently run AI/ML applications. Our services encompass GPU-intensive cloud computing, AI/ML platforms like TIR built on Jupyter Notebook, Linux and Windows cloud solutions, storage cloud with automated backups, and cloud solutions with pre-installed frameworks. E2E Networks emphasizes a high-value, top-performance infrastructure, boasting a 90% cost reduction in monthly cloud bills for clients. Our multi-region cloud is designed for performance, reliability, resilience, and security, serving over 15,000 clients. Additional features include block storage, load balancers, object storage, one-click deployment, database-as-a-service, API & CLI access, and a content delivery network.
    Starting Price: $0.012 per hour
  • 7
    Amazon SageMaker Model Building
    Amazon SageMaker provides all the tools and libraries you need to build ML models, the process of iteratively trying different algorithms and evaluating their accuracy to find the best one for your use case. In Amazon SageMaker you can pick different algorithms, including over 15 that are built-in and optimized for SageMaker, and use over 150 pre-built models from popular model zoos available with a few clicks. SageMaker also offers a variety of model-building tools including Amazon SageMaker Studio Notebooks and RStudio where you can run ML models on a small scale to see results and view reports on their performance so you can come up with high-quality working prototypes. Amazon SageMaker Studio Notebooks help you build ML models faster and collaborate with your team. Amazon SageMaker Studio notebooks provide one-click Jupyter notebooks that you can start working within seconds. Amazon SageMaker also enables one-click sharing of notebooks.
  • 8
    Amazon SageMaker Studio Lab
    Amazon SageMaker Studio Lab is a free machine learning (ML) development environment that provides the compute, storage (up to 15GB), and security, all at no cost, for anyone to learn and experiment with ML. All you need to get started is a valid email address, you don’t need to configure infrastructure or manage identity and access or even sign up for an AWS account. SageMaker Studio Lab accelerates model building through GitHub integration, and it comes preconfigured with the most popular ML tools, frameworks, and libraries to get you started immediately. SageMaker Studio Lab automatically saves your work so you don’t need to restart in between sessions. It’s as easy as closing your laptop and coming back later. Free machine learning development environment that provides the computing, storage, and security to learn and experiment with ML. GitHub integration and preconfigured with the most popular ML tools, frameworks, and libraries so you can get started immediately.
  • 9
    Clore.ai

    Clore.ai

    Clore.ai

    ​Clore.ai is a decentralized platform that revolutionizes GPU leasing by connecting server owners with renters through a peer-to-peer marketplace. It offers flexible, cost-effective access to high-performance GPUs for tasks such as AI development, scientific research, and cryptocurrency mining. Users can choose between on-demand leasing, which ensures uninterrupted computing power, and spot leasing, which allows for potential interruptions at a lower cost. It utilizes Clore Coin (CLORE), an L1 Proof of Work cryptocurrency, to facilitate transactions and reward participants, with 40% of block rewards directed to GPU hosts. This structure enables hosts to earn additional income beyond rental fees, enhancing the platform's appeal. Clore.ai's Proof of Holding (PoH) system incentivizes users to hold CLORE coins, offering benefits like reduced fees and increased earnings. It supports a wide range of applications, including AI model training, scientific simulations, etc.
  • 10
    Lambda

    Lambda

    Lambda

    Lambda provides high-performance supercomputing infrastructure built specifically for training and deploying advanced AI systems at massive scale. Its Superintelligence Cloud integrates high-density power, liquid cooling, and state-of-the-art NVIDIA GPUs to deliver peak performance for demanding AI workloads. Teams can spin up individual GPU instances, deploy production-ready clusters, or operate full superclusters designed for secure, single-tenant use. Lambda’s architecture emphasizes security and reliability with shared-nothing designs, hardware-level isolation, and SOC 2 Type II compliance. Developers gain access to the world’s most advanced GPUs, including NVIDIA GB300 NVL72, HGX B300, HGX B200, and H200 systems. Whether testing prototypes or training frontier-scale models, Lambda offers the compute foundation required for superintelligence-level performance.
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