We performed a comparison between OpenVINO and TensorFlow based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models."
"The initial setup is quite simple."
"The inferencing and processing capabilities are quite beneficial for our requirements."
"I would rate the solution an eight out of ten. I am not a developer but more of an account manager. I can find what I want with TensorFlow. I haven’t contacted technical support for any issues. Since TensorFlow is vastly documented on the internet, I usually find some good websites where people exchange their views about the solution and apply that."
"TensorFlow improves my organization because our clients get a lot of investment from their investors and we are progressively improving the products. Every six months we release new features."
"It provides us with 35 features like patch normalization layers, and it is easy to implement using the Kras library when the Kaspersky flow is running behind it."
"Our clients were not aware they were using TensorFlow, so that aspect was transparent. I think we personally chose TensorFlow because it provided us with more of the end-to-end package that you can use for all the steps regarding billing and our models. So basically data processing, training the model, evaluating the model, updating the model, deploying the model and all of these steps without having to change to a new environment."
"It is also totally Open-Source and free. Open-source applications are not good usually. but TensorFlow actually changed my view about it and I thought, "Look, Oh my God. This is an open-source application and it's as good as it could be." I learned that TensorFlow, by sharing their own knowledge and their own platform with other developers, it improved the lives of many people around the globe."
"The most valuable features are the frameworks and the functionality to work with different data, even when we have a certain quantity of data flowing."
"Edge computing has some limited resources but TensorFlow has been improving in its features. It is a great tool for developers."
"It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions."
"The model optimization is a little bit slow — it could be improved."
"At this point, the product could probably just use a greater integration with more machine learning model tools."
"It has some disadvantages because when you're working with very complex models, neural networks if OpenVINO cannot convert them automatically and you have to do a custom layer and later add it to the model. It is difficult."
"I know this is out of the scope of TensorFlow, however, every time I've sent a request, I had to renew the model into RAM and they didn't make that prediction or inference. This makes the point for the request that much longer. If they could provide anything to help in this part, it will be very great."
"However, if I want to change just one thing in the implementation of TensorFlow functions I have to copy everything that they wrote and I change it manually if indeed it can be amended. This is really hard as it's written in C++ and has a lot of complications."
"There are a lot of problems, such as integrating our custom code. In my experience model tuning has been a bit difficult to edit and tune the graph model for best performance. We have to go into the model but we do not have a model viewer for quick access."
"For newcomers to the field, the learning curve can be steep, often requiring about a year of dedicated effort."
"It would be nice to have more pre-trained models that we can utilize within layers. I utilize a Mac, and I am unable to utilize AMD GPUs. That's something that I would definitely be like to be able to access within TensorFlow since most of it is with CUDA ML. This only matters for local machines because, in Azure, you can just access any GPU you want from the cloud. It doesn't really matter, but the clients that I work with don't have cloud accounts, or they don't want to utilize that or spend the money. They all see it as too expensive and want to know what they can do on their local machines."
"It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers."
"I would love to have a user interface like a programming interface. You need to have a set of menus where you can put things together in a graphical interface. The complete automation of the integration of the modules would also be interesting. It’s more like plumbing as opposed to a fully automated environment."
"TensorFlow Lite only outputs to C."
Earn 20 points
OpenVINO is ranked 11th in AI Development Platforms while TensorFlow is ranked 4th in AI Development Platforms with 16 reviews. OpenVINO is rated 8.6, while TensorFlow is rated 9.0. The top reviewer of OpenVINO writes "A free toolkit providing improved neural network performance". On the other hand, the top reviewer of TensorFlow writes "Effective deep learning, free to use, and highly stable". OpenVINO is most compared with PyTorch, Azure OpenAI, Google Cloud AI Platform, Google Vertex AI and Microsoft Azure Machine Learning Studio, whereas TensorFlow is most compared with Microsoft Azure Machine Learning Studio, Google Vertex AI, IBM Watson Machine Learning, Hugging Face and Azure OpenAI. See our OpenVINO vs. TensorFlow report.
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