--- title: Deep Learning VM Image Reviews meta\_title: 'Deep Learning VM Image Reviews 2026: Details, Pricing, & Features | G2' meta\_description: Filter 58 reviews by the users' company size, role or industry to find out how Deep Learning VM Image works for a business like yours. aggregate\_rating: rating\_value: 4.4 review\_count: 58 scale: '5' date\_modified: '2026-08-09' parent\_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence --- # Deep Learning VM Image Reviews & Product Details Claimed ###### Profile Status This profile is currently managed by Deep Learning VM Image but has limited features. Are you part of the Deep Learning VM Image team? [Upgrade your plan](https://sell.g2.com) to enhance your branding and engage with visitors to your profile! Deep Learning VM Images are pre-configured virtual machine images optimized for data science and machine learning tasks. These images come with essential machine learning frameworks and tools pre-installed, enabling users to deploy and scale machine learning models efficiently on Google Cloud's infrastructure. Key Features and Functionality: - Pre-installed Frameworks: Support for TensorFlow Enterprise, TensorFlow, PyTorch, and generic high-performance computing, catering to various machine learning needs. - Operating System Options: Based on Debian 11 and Ubuntu 22.04, providing flexibility and compatibility with different environments. - Comprehensive Python Environment: Includes Python 3.10 with a suite of libraries such as NumPy, SciPy, Matplotlib, Pandas, NLTK, Pillow, scikit-image, OpenCV, and scikit-learn, facilitating a robust development experience. - JupyterLab Integration: Offers JupyterLab notebook environments for rapid prototyping and interactive development. - GPU Acceleration: Equipped with the latest NVIDIA drivers and packages, including CUDA 11.x and 12.x, CuDNN, and NCCL, to leverage GPU capabilities for accelerated computation. Primary Value and User Solutions: Deep Learning VM Images streamline the setup process for machine learning projects by providing ready-to-use environments with pre-installed frameworks and tools. This reduces the time and effort required for configuration, allowing data scientists and machine learning practitioners to focus on model development and experimentation. The integration with Google Cloud's scalable infrastructure ensures that users can efficiently manage and scale their machine learning workloads, whether they require CPU or GPU resources. Regular updates and community support further enhance the reliability and performance of these VM images, making them a valuable resource for accelerating machine learning initiatives. * * * Seller [Google](https://www.g2.com/sellers/google) Discussions [Deep Learning VM Image Community](https://www.g2.com/products/deep-learning-vm-image/discuss) Solution Type Best-of-Breed Overview by Altaf Shaikh (Executive Supply Chain operations | Ex- Metro Brands LTD -Data Analyst) Show More ## Top-Rated Alternatives [ ![VMware vSphere](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "VMware vSphere") VMware vSphere 4.5/5(768) ](https://www.g2.com/products/vmware-vsphere/reviews) [ ![VMware Cloud Foundation (VCF)](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "VMware Cloud Foundation (VCF)") VMware Cloud Foundation (VCF) 4.4/5(691) ](https://www.g2.com/products/vmware-cloud-foundation-vcf/reviews) [ ![Azure Virtual Machines](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Azure Virtual Machines") Azure Virtual Machines 4.4/5(393) ](https://www.g2.com/products/azure-virtual-machines/reviews) [ View All Alternatives ](https://www.g2.com/products/deep-learning-vm-image/competitors/alternatives) ## User Insights Average based on 58 real user reviews. [Log in to unlock pricing and user insights](/login) ## Deep Learning VM Image Integrations (2) What do users say about integrations? Integration information sourced from real user reviews. [ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Docker ](https://www.g2.com/products/docker-inc-docker/reviews)[ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") Google Workspace ](https://www.g2.com/products/google-workspace/reviews) Show More ![Subhashree S.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Subhashree S.") SS Subhashree S. Developer Enterprise (\> 1000 emp.) 8/7/2026 "Pre-Configured, GPU-Ready ML Environment That Speeds Up Deep Learning on Google Cloud" 4.5/5 What do you like best about Deep Learning VM Image? What I like best about Deep Learning VM Image is that it provides a pre-configured environment for machine learning and deep learning development. It comes with popular frameworks, libraries, drivers, and tools already installed, which significantly reduces setup time. The ability to quickly create GPU-enabled environments, experiment with different models, and scale workloads on Google Cloud makes it highly valuable for AI development and research. Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? What I dislike about Deep Learning VM Image is that the pre-configured environments can sometimes become difficult to customize when specific versions of frameworks, libraries, or dependencies are required. Managing updates and compatibility between different ML packages can require additional effort. The cost of running GPU-enabled VM instances can also become high for continuous workloads, especially for large-scale experiments. Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? Deep Learning VM Image solves the challenge of setting up and managing complex machine learning development environments. It provides pre-configured VMs with popular ML frameworks, libraries, CUDA drivers, and GPU support, reducing the time and effort required for manual installation and configuration. This benefits me by enabling faster experimentation, improving developer productivity, and allowing teams to focus more on building and training models rather than managing infrastructure. Review collected by and hosted on G2.com. Show More Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.G2 IconCurrent UserValidated ReviewerIncentivizedSource: G2 invite ![Muhammed A.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Muhammed A.") MA Muhammed A. Technical Project Manager Information Technology and Services Mid-Market (51-1000 emp.) 8/6/2026 "Fast, Preconfigured GPU Training Environments with Smooth Google Cloud Integration" 4.5/5 What do you like best about Deep Learning VM Image? Google Deep Learning VM Image made it much faster to get a fully configured training environment running for model development, with common frameworks and drivers pre-installed instead of setting everything up manually. Having GPU support ready out of the box removed a lot of the setup friction that usually eats up time early in a training project. The interface for launching and managing instances is straightforward, and integration with the rest of our Google Cloud stack was smooth, since deployment fit naturally into infrastructure we were already using. Performance for training workloads has been solid, with GPU acceleration handling compute-intensive tasks efficiently. Pricing has offered reasonable ROI given the time saved on environment setup, and onboarding required minimal effort since the pre-configured images worked reliably from the start. Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? Image sizes and initial boot times are heavier compared to a minimal custom VM, which added some startup delay when spinning up new instances frequently. Costs for GPU-enabled instances can add up quickly during extended training runs, requiring careful monitoring to avoid leaving instances running unnecessarily. Customizing beyond the pre-configured framework versions sometimes required extra steps to install specific package versions not included by default. Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? Google Deep Learning VM Image removed a lot of the environment setup overhead when starting model training, letting us focus on actual model development instead of configuring frameworks and GPU drivers from scratch. This has made our training workflow more consistent and predictable, cutting down on environment-related issues that used to slow down early iteration. Review collected by and hosted on G2.com. Show More Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.G2 IconCurrent UserValidated ReviewerIncentivizedSource: G2 invite ![LOKESH G.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "LOKESH G.") LG LOKESH G. Engineer.SGB TCS-FS CORE BANKING,Production Information Technology and Services Enterprise (\> 1000 emp.) 7/23/2026 "Preconfigured GPU AI Environment That Speeds Up Deep Learning on Google Cloud" 4.5/5 What do you like best about Deep Learning VM Image? It provides a pre-configured environment with popular AI and machine learning frameworks already installed, which eliminates lengthy setup and dependency management. It also makes it easy to start training and experimenting with models on GPU-enabled virtual machines, while still supporting customization for different workloads. Integration with cloud storage and other Google Cloud services is smooth, and overall it significantly speeds up development, prototyping, and deployment for deep learning projects. Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? Managing environments and package dependencies can become challenging as projects evolve, especially when multiple framework versions are required. The initial setup for advanced networking or GPU optimization may also demand some cloud expertise. In addition, running GPU-enabled VM instances can get expensive for long-running workloads, and keeping images up to date with the latest drivers and frameworks sometimes still requires manual maintenance. Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? Deep Learning VM Image streamlines the otherwise time-consuming process of setting up and configuring machine learning environments by offering pre-installed frameworks, GPU drivers, and development tools. With everything ready to go, I can start training and testing models right away instead of spending hours on environment setup and dependency management. As a result, my development cycles move faster, experimentation is more efficient, and deploying AI workloads on cloud infrastructure becomes much simpler. Review collected by and hosted on G2.com. Show More Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.G2 IconCurrent UserValidated ReviewerIncentivizedSource: G2 invite ![Sattwik M.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Sattwik M.") SM Sattwik M. Review Freelancer(Specialist) Mid-Market (51-1000 emp.) 8/4/2026 "Ready to Use Deep Learning Environment That Saves Time" 4.5/5 What do you like best about Deep Learning VM Image? What I like best about Deep Learning VM Image is that it eliminates the time and complexity of setting up a deep learning environment from scratch. The UI within Google Cloud is straightforward, making it easy to deploy and manage virtual machines, while the onboarding experience is supported by clear documentation and preconfigured environments. The image comes with popular AI and machine learning frameworks such as TensorFlow, PyTorch, CUDA, cuDNN, and Jupyter Notebook already installed, allowing projects to start quickly without dealing with dependency conflicts. It integrates seamlessly with other Google Cloud services like Cloud Storage, Vertex AI, and Compute Engine, creating an efficient workflow for model development and experimentation. Performance is reliable, particularly when using GPU-enabled instances for training and inference workloads. From a pricing perspective, the preconfigured environment saves considerable setup time and reduces operational overhead, providing a strong return on investment for teams working on AI projects. Overall, the combination of ready-to-use AI tools, solid performance, cloud integrations, and streamlined management makes Deep Learning VM Image a practical solution for machine learning development. Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? While Deep Learning VM Image significantly simplifies environment setup, there are a few areas that could be improved. The UI is functional but can feel overwhelming for users who are new to Google Cloud or cloud-based machine learning workflows. Some advanced configuration options require familiarity with Compute Engine, networking, and resource management, which increases the learning curve during onboarding. Although the preconfigured integrations with Google Cloud services work well, extending workflows to third-party tools may require additional manual configuration. GPU instances deliver excellent performance but can become expensive for long-running workloads, so careful resource management is necessary to achieve a good return on investment. The AI frameworks are comprehensive, but keeping track of framework versions and compatibility across projects can sometimes be challenging. More guided setup resources and troubleshooting documentation would further improve the overall user experience. Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? Deep Learning VM Image solves the time-consuming process of configuring and maintaining machine learning environments. Instead of manually installing AI frameworks, GPU drivers, CUDA libraries, and dependencies, it provides a preconfigured environment that is ready for model development and training. Its seamless integration with Google Cloud services also simplifies data storage, compute management, and deployment workflows. For me, this meant spending less time on infrastructure setup and more time experimenting with models and validating ideas. The optimized environment delivered reliable performance for GPU-based workloads, while the built-in AI frameworks accelerated development. Although cloud resources require cost monitoring, the reduction in setup effort, maintenance, and compatibility issues provides a strong return on investment for AI and deep learning projects. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Parth P.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Parth P.") PP Parth P. Software Engineer Mid-Market (51-1000 emp.) 7/28/2026 "Optimized Performance for DS & ML Tasks, Even on Lower-End Engines" 4.5/5 What do you like best about Deep Learning VM Image? It’s optimized to deliver strong performance for DS and ML tasks, which means even lower-end engines can produce better outputs. Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? the pricing is little steep and sometimes it's hard to tune images more Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? it helps us deploy instances that are doing DS tasks for predictions. It reduces need for larger instance since it's optimized for DS taks Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Sergio R.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Sergio R.") SR Sergio R. DevOps Engineer Small-Business (50 or fewer emp.) 7/3/2025 "A Turnkey Powerhouse for Deep Learning—Ready from the Start" 4.5/5 What do you like best about Deep Learning VM Image? What I love: Instant, GPU‑ready environment – Out of the box, these VM images include the full ML stack: TensorFlow, PyTorch, scikit‑learn, CUDA, cuDNN, NCCL, NVIDIA drivers, JupyterLab, and more Wide framework and hardware support – Choose from CPUs or GPUs, and frameworks like TensorFlow Enterprise, PyTorch, HPC images—it’s easy to match your hardware and software needs Smooth integration with Google Cloud – Seamless links to BigQuery, Vertex AI, Cloud Storage, and other services keep my workflow fluid and efficient Zero setup time – The time saved from bypassing manual installs of drivers, frameworks, and Jupyter is huge—educes friction and eliminates compatibility headaches Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? While the Deep Learning VM Image is powerful and saves a lot of setup time, there are some areas for improvement: Costs can escalate quickly, especially when using GPU instances for long-running jobs or accidentally leaving VMs running. Customization is sometimes limited; installing very specific package versions or uncommon libraries can break pre-configured dependencies. Startup times for large VMs (especially with GPUs) can occasionally feel slow compared to some other cloud providers. Managing quota limits and regional availability of GPUs sometimes interrupts workflows if capacity is limited in a zone. It’s a great tool for Google Cloud users, but users coming from AWS or Azure might face a learning curve with GCP’s networking and IAM model. Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? Eliminates environment setup time: Installing deep learning libraries (TensorFlow, PyTorch, CUDA, etc.) and configuring GPU drivers manually can be time-consuming and error-prone. Deep Learning VM Image comes fully pre-configured and ready to use. Simplifies GPU usage: Managing GPU compatibility (CUDA/cuDNN versions) is challenging, but Deep Learning VM Image solves this with pre-tested, optimized configurations. Streamlines scalability: I can quickly spin up powerful machines when I need them and shut them down when I'm done—no need to maintain expensive on-prem hardware. Enables fast experimentation: Pre-installed JupyterLab lets me prototype and test ideas without delay. 🔹 How it benefits me: I save hours of setup time, letting me focus on developing and training models instead of configuring environments. I can access powerful GPUs on demand, speeding up training for large neural networks. Integrated Google Cloud tools help me move faster from experiment to production, improving my ML workflow efficiency. It reduces my infrastructure overhead and allows for cost-effective scaling, since I only pay for what I use. Review collected by and hosted on G2.com. Show More Validated ReviewerSource: Organic ![Dhanush N.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Dhanush N.") DN Dhanush N. Data Scientist Mid-Market (51-1000 emp.) 7/14/2025 "Powerful, preconfigured VM for seamless deep learning development and training." 5/5 What do you like best about Deep Learning VM Image? What I like best about Deep Learning VM Image is the instant access to pre-installed, optimized ML frameworks with GPU support, which saves tons of setup time and lets me start training models immediately. Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? What I dislike about Deep Learning VM Image is that costs can add up quickly with GPU usage if not carefully managed, especially for long-running experiments. A built-in usage estimator or auto-shutdown option would be helpful. Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? Deep Learning VM Image solves the problem of complex environment setup by providing a fully configured, GPU-optimized machine with all major ML/DL frameworks pre-installed. This saves me hours of configuration time and allows me to focus entirely on model development, experimentation, and training—boosting productivity and accelerating project timelines. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Shantanu R.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Shantanu R.") SR Shantanu R. Engineer Small-Business (50 or fewer emp.) 12/17/2024 "A single platform for your AI needs" 4.5/5 What do you like best about Deep Learning VM Image? It offers a wide range of features but specifically, I liked the feature of every framework to make a machine learning or Artificial Intelligence project like Tensorflow, PyTorch, Keras, etc. It offers different tools as well to integrate it very easily and efficiently. As this platform is given by Google Cloud it is quite obvious that it can be used and hosted on any platform. I have used its free trial for a month where i got to know the benefits of it, later it charges on besis of what you have used. Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? The pricing based on the usage sometimes gets you where you will get a high amount to pay. Also it requires a good amount of data and a quality internet connection to use its all feature efficiently with lowest latency/delay. Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? I see that they thought of a very good idea to host all the frameworks on cloud and to provide these all the needed tools to make it efficient to make projects. It also gives a free trial to make oneself used to the UI and GUI and all the customizations. As a beginner I believe that it is a good platform. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: G2 invite AG Allabakash G. AI developer Mid-Market (51-1000 emp.) 11/20/2024 "Deep learning VM image come with pre installed tools which help in building machine learning models." 4.5/5 What do you like best about Deep Learning VM Image? The most thing i like about this image is that the VM created from google with this image that most important libraries, nvida cuda toolkit all this tools are already no headache of installing all of this from scratch, once this VM initialized Data scientist or ML engineer can directly start on training or building the Models, Google has really good customer support where they help us on creating this VM if we are stuck somewhere, apart from that we also have good step by step documentation for setting up, and it is really easy to setup a new VM in Google cloud with Deep Learning VM image Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? As of now i dont have any that important dislikes towards DeepLearning VM Image. But one thing is if Ubuntu os is created there will be no RDP, that is the different case where you can create a RDP of ubuntu os but working through RDP will be really slow that is the different case when you have a good internet connection. one more concern is the pricing for me Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? When a new VM is initiated the main thing will be to install nvidia container toolkit some necessary libraries some necessary tools like nvidia toolkits where you should install it by keeping in mind which cuda version is there in the VM with the help of that we should install all this, but with the help of this image their is no necessary to install this because all this is already installed we can jsut get started on the main thing for which we had created this VM. In the end it saves lot of time Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: G2 invite ![Seerapu N.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Seerapu N.") SN Seerapu N. Node JS/Nest JS Developer Mid-Market (51-1000 emp.) 3/26/2025 "Deep Learning for the Deepest and the challenging AI projects that disrupts the markets." 5/5 What do you like best about Deep Learning VM Image? I really like the pre-configured environment of Deep Learning VM Image. It also provides the high capability computing environment that enabling to take up tasks with ease. Review collected by and hosted on G2.com. What do you dislike about Deep Learning VM Image? configuration at times it not always match specific project requirements. In such scenarios it takes time and effort to configure such cases. Review collected by and hosted on G2.com. What problems is Deep Learning VM Image solving and how is that benefiting you? It solves the problem of setting up a complex deep learning environment and allows me to focus more on model development and experimentation, enhancing productivity and efficiency. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: G2 invite ##### Pricing Pricing details for this product isn’t currently available. Visit the vendor’s website to learn more. [ View More Pricing Information ](https://www.g2.com/products/deep-learning-vm-image/pricing) ##### ##### Deep Learning VM Image Features Model Development Language Support Drag and Drop Pre-Built Algorithms Machine/Deep Learning Services Computer Vision Natural Language Processing Natural Language Generation Deployment Managed Service Application Scalability System Data Ingestion & Wrangling [ View More Features ](https://www.g2.com/products/deep-learning-vm-image/features) ##### Categories on G2 [Infrastructure as a Service (IaaS)](https://www.g2.com/categories/infrastructure-as-a-service-iaas)[Data Science and Machine Learning Platforms](https://www.g2.com/categories/data-science-and-machine-learning-platforms)[Server Virtualization](https://www.g2.com/categories/server-virtualization) ##### Explore More [Which is the most trusted enterprise mobility management by IT admins at financial services firms based on user reviews?](https://www.g2.com/discussions/which-is-the-most-trusted-enterprise-mobility-management-by-it-admins-at-financial-services-firms-based-on-user-reviews)[What is the best AI writing tool for company blogs?](https://www.g2.com/discussions/what-is-the-best-ai-writing-tool-for-company-blogs)[Best desktop solutions for managing sales performance](https://www.g2.com/discussions/best-desktop-solutions-for-managing-sales-performance) [What is the best employee engagement software?](https://www.g2.com/discussions/what-is-the-best-employee-engagement-software)[User-friendly accounting software with payroll capabilities](https://www.g2.com/discussions/what-s-the-most-user-friendly-accounting-software-with-payroll-capabilities)[Pros and Cons Details](https://www.g2.com/products/deep-learning-vm-image/reviews?qs=pros-and-cons) [Show MoreShow Less](javascript:void(0);)