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 inferencing and processing capabilities are quite beneficial for our requirements."
"The initial setup is quite simple."
"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."
"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."
"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."
"What made TensorFlow so appealing to us is that you could run it on a cluster computer and on a mobile device."
"It's got quite a big community, which is useful."
"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."
"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."
"Google is behind TensorFlow, and they provide excellent documentation. It's very thorough and very helpful."
"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."
"Personally, I find it to be a bit too much AI-oriented."
"The solution is hard to integrate with the GPUs."
"It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers."
"In terms of improvement, we always look for ways they can optimize the model, accelerate the speed and the accuracy, and how can we optimize with our different techniques. There are various techniques available in TensorFlow. Maintaining accuracy is an area they should work on."
"JavaScript is a different thing and all the websites and web apps and all the mobile apps are built-in JavaScript. JavaScript is the core of that. However, TensorFlow is like a machine learning item. What can be improved with TensorFlow is how it can mix in how the JavaScript developers can use TensorFlow."
"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."
"TensorFlow Lite only outputs to C."
"It would be nice if the solution was in Hungarian. I would like more Hungarian NAT models."
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, Hugging Face, Azure OpenAI and IBM Watson Machine Learning. See our OpenVINO vs. TensorFlow report.
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