It's been two months since this profile received a new review

Deep Learning VM Image Reviews & Product Details

Deep Learning VM Images are pre-configured virtual machine instances on Google Cloud, designed to streamline the development and deployment of machine learning models. These images come equipped with popular frameworks such as TensorFlow, PyTorch, and scikit-learn, along with essential tools like Jupyter Notebook and CUDA for GPU acceleration. By providing an optimized environment out of the box, Deep Learning VM Images enable data scientists and developers to focus on building and training models without the overhead of setting up and maintaining the underlying infrastructure. Key Features and Functionality: - Pre-installed Frameworks: Includes TensorFlow, PyTorch, and scikit-learn, facilitating immediate model development. - Integrated Development Tools: Comes with Jupyter Notebook for interactive coding and visualization. - GPU Support: Optimized for NVIDIA GPUs with CUDA and cuDNN, enhancing computational performance. - Customizable Configurations: Offers flexibility to choose machine types and resources based on project requirements. - Regular Updates: Ensures access to the latest versions of frameworks and tools, maintaining compatibility and performance. Primary Value and Problem Solved: Deep Learning VM Images address the challenge of setting up and managing complex machine learning environments. By offering a ready-to-use, optimized platform, they reduce the time and effort required for environment configuration, allowing users to concentrate on developing, training, and deploying machine learning models efficiently. This solution is particularly beneficial for teams seeking to accelerate their AI initiatives without the complexities of infrastructure management.

Seller

Google

Product Description

Top-Rated Alternatives

Azure Virtual Machines

View All Alternatives

Deep Learning VM Image Integrations

(1)

Integration information sourced from real user reviews.

Deep Learning VM Image Reviews (50)

G2 reviews are authentic and verified.

Here's how.

Abhishek J.

10/18/2025

"Efficient for Deep Learning, Needs Streamlined Dependency Management"

4/5

What do you like best about Deep Learning VM Image?

{"I love using Deep Learning VMSS for model training and inferences because it comes with all the pre-trained models and pre-installed dependencies, which eliminates the hassle of setting up the environment and allows me to start working directly.","I appreciate that Deep Learning VMSS is well integrated with Google Cloud Platform, making it easier for us to integrate with our GCP VMs.","I find that Deep Learning VMSS saves time by eliminating the need to reinstall custom dependencies and setting up environments, allowing me to focus more on business-related tasks.","I enjoy the multiple options available in Deep Learning VMSS to select Python and TensorFlow versions and the ability to install or reinstall dependencies, providing flexibility and ensuring I can work with the specific configurations I need.","I like that the setup process for Deep Learning VMSS is very easy, just selecting an image and booting a virtual machine, which simplifies the startup process significantly."} Review collected by and hosted on G2.com.

What do you dislike about Deep Learning VM Image?

I find that the inclusion of numerous unnecessary dependencies can make the VM image feel bloated if those dependencies aren't relevant to my tasks. This results in a sense of inefficiency as some dependencies might not be in use, which isn't ideal for my specific projects. Review collected by and hosted on G2.com.

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.

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.

Shantanu R.

GDSC Core Team

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.

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.

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.

Altaf S.

Executive Supply Chain Operations

Small-Business (50 or fewer emp.)

8/3/2025

"Efficient and Scalable"

4/5

What do you like best about Deep Learning VM Image?

Ready-to-Use Environment,

Optimized for Performance,

Seamless Integration,

Security & Updates, Review collected by and hosted on G2.com.

What do you dislike about Deep Learning VM Image?

Limited Customization at First,

Cost Sensitivity,

Dependency Entanglements,

Needs Strong Internet Review collected by and hosted on G2.com.

Verified User in Real Estate

Mid-Market (51-1000 emp.)

11/22/2024

"Lets say goodbye to setting up a dev env for your deep learning projects"

4.5/5

What do you like best about Deep Learning VM Image?

Deep Learning VM instances come pre-installed with popular ML frameworks, optimized drivers, and tools. This eliminates setup headaches and ensures compatibility. Review collected by and hosted on G2.com.

What do you dislike about Deep Learning VM Image?

One must have GCP exprience to work on or setup Google Deep learning VM Review collected by and hosted on G2.com.

What problems is Deep Learning VM Image solving and how is that benefiting you?

Following are the problems that my team was facing before this setup

1. Setting up a development environment for deep learning: Google Deep Learning VM instances come pre-installed with popular ML frameworks, optimized drivers, and tools. This eliminates setup headaches and ensures compatibility.

2. Training models on local machines was very slow: These VMs offer access to powerful GPUs (e.g., NVIDIA Tesla series) and TPUs, significantly accelerating model training and inference at scale. Review collected by and hosted on G2.com.

Rizwan K.

Channel sales specialist

Mid-Market (51-1000 emp.)

11/21/2024

Business partner of the seller or seller's competitor, not included in G2 scores.

"Integration with Google Cloud Services"

5/5

What do you like best about Deep Learning VM Image?

Perfectly complements services like Google AI Platform, BigQuery, and Cloud Storage, streamlining workflows. It is easy of implement, even for beginners, and the VM image is user-friendly with excellent documentation and tutorials. Some users may find default resource allocations too high for smaller-scale projects. Supports NVIDIA GPUs and TPUs for faster model training and inference. Perfectly Integration services like Google AI Platform, BigQuery, and Cloud Storage, streamlining workflows. You can get your answer with customer support team. You can frequency use this even for big task. Review collected by and hosted on G2.com.

What do you dislike about Deep Learning VM Image?

No, since I use I haven't find anything which is difficult to use. Review collected by and hosted on G2.com.

What problems is Deep Learning VM Image solving and how is that benefiting you?

The Google Deep Learning VM Image offers a seamless and robust platform for professionals in AI, machine learning, and deep learning. Pre-configured with popular frameworks like TensorFlow, PyTorch, and Jupyter Notebook, it minimizes setup time and allows developers to focus on building and testing their models. Review collected by and hosted on G2.com.

Leonardo C.

Paid media analytic

Small-Business (50 or fewer emp.)

11/19/2024

"Google Deep Learning VM Image stands out as a top-tier solution for AI practitioners"

4.5/5

What do you like best about Deep Learning VM Image?

This ease of use, paired with Google Cloud’s reliable infrastructure, allows teams to focus more on experimentation and innovation rather than managing dependencies and configurations. Review collected by and hosted on G2.com.

What do you dislike about Deep Learning VM Image?

the tight integration with Google Cloud services, while convenient, can feel restrictive for teams preferring a multi-cloud approach or needing to migrate workloads to other cloud providers 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 accessing high-performance compute resources like GPUs and TPUs, offering seamless scalability for training large and complex models. Users benefit by being able to efficiently handle resource-intensive workloads without needing to invest in costly on-premises hardware. Review collected by and hosted on G2.com.