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 inferencing and processing capabilities are quite beneficial for our requirements."
"The initial setup is quite simple."
"The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models."
"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."
"It's got quite a big community, which is useful."
"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."
"It is open-source, and it is being worked on all the time. You don't have to pay all the big bucks like Azure and Databricks. You can just use your local machine with the open-source TensorFlow and create pretty good models."
"TensorFlow provides Insights into both data and machine learning strategies."
"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."
"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."
"It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers."
"There are connection issues that interrupt the download needed for the data sets. We need to prepare them ourselves."
"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."
"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."
"Personally, I find it to be a bit too much AI-oriented."
"It would be nice if the solution was in Hungarian. I would like more Hungarian NAT models."
"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."
"It doesn't allow for fast the proto-typing. So usually when we do proto-typing we will start with PyTorch and then once we have a good model that we trust, we convert it into TensorFlow. So definitely, TensorFlow is not very flexible."
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.
See our list of best AI Development Platforms vendors.
We monitor all AI Development Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.