Compare OpenVINO vs. TensorFlow

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OpenVINO Logo
207 views|181 comparisons
TensorFlow Logo
808 views|713 comparisons
Most Helpful Review
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"It reduces the required processing power on the CPU and GPU. With OpenVINO, you can run your normal algorithms and normal software on CPU, but don't require a huge amount of processor power. It is faster, and you have plenty of more resources for other jobs. It is easy to manage the software with OpenVINO. You can change the number of models or quotes. I can use five quotes for a model, or I can write a particular model with a quote. Management is easy without touching the software.""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."

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"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.""TensorFlow is a framework that makes it really easy to use for deep learning.""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.""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."

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Cons
"Their resolution time for certain kinds of issues could be better. I had a problem during the implementation, and it took them two or three months to resolve it. I wasted so much time. If it is a simple problem or implementation issue, they will provide the answers and solve it quickly, but if there are some problems with the product, it can take time.""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.""The model optimization is a little bit slow — it could be improved."

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"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.""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.""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.""There are connection issues that interrupt the download needed for the data sets. We need to prepare them ourselves.""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."

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Pricing and Cost Advice
"Specifically for our products, it was costly to use OpenVINO without using the OpenVINO hardware. This was because we had not used the same number of CPUs. We had reduced the CPU number, but we didn't reduce it too much. Therefore, the cost was more with OpenVINO, but the efficiency was also much higher. We didn't have any problems with CPU usage or memory usage. OpenVINO really helped us with these issues.""We didn't have to pay for any licensing with Intel OpenVINO. Everything is available on their site and easily downloadable for free."

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"TensorFlow is free.""I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free.""We are using the free version."

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Ranking
3rd
Views
207
Comparisons
181
Reviews
2
Average Words per Review
743
Avg. Rating
8.5
2nd
Views
808
Comparisons
713
Reviews
5
Average Words per Review
1,059
Avg. Rating
8.8
Popular Comparisons
Compared 11% of the time.
Compared 5% of the time.
Compared 4% of the time.
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OpenVINO
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TensorFlow
Overview

OpenVINO toolkit quickly deploys applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends computer vision (CV) workloads across Intel hardware, maximizing performance. The OpenVINO toolkit includes the Deep Learning Deployment Toolkit (DLDT).

TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.

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Sample Customers
Information Not Available
Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm
Top Industries
VISITORS READING REVIEWS
Comms Service Provider41%
Manufacturing Company20%
Computer Software Company20%
Government6%
VISITORS READING REVIEWS
Comms Service Provider45%
Computer Software Company19%
Manufacturing Company14%
K 12 Educational Company Or School4%

OpenVINO is ranked 3rd in AI Development Platforms with 3 reviews while TensorFlow is ranked 2nd in AI Development Platforms with 5 reviews. OpenVINO is rated 8.6, while TensorFlow is rated 8.8. The top reviewer of OpenVINO writes "Fast, reduces the required processing power, and easy to manage". On the other hand, the top reviewer of TensorFlow writes "The generator saves us a lot of time and memory in terms of development and the learning process of models". OpenVINO is most compared with , whereas TensorFlow is most compared with Microsoft Azure Machine Learning Studio, Wit.ai, Infosys Nia and Caffe.

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