We performed a comparison between OpenVINO and PyTorch based on real PeerSpot user reviews.
Find out what your peers are saying about Microsoft, Google, TensorFlow and others in AI Development Platforms."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."
"The tool is very user-friendly."
"yTorch is gaining credibility in the research space, it's becoming easier to find examples of papers that use PyTorch. This is an advantage for someone who uses PyTorch primarily."
"Its interface is the most valuable. The ability to have an interface to train machine learning models and construct them with the high-level interface, without excess busting and reconstructing the same technical elements, is very useful."
"It's been pretty scalable in terms of using multiple GPUs."
"The framework of the solution is valuable."
"I like that PyTorch actually follows the pythonic way, and I feel that it's quite easy. It's easy to find compared to others who require us to type a long paragraph of code."
"The model optimization is a little bit slow — it could be improved."
"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."
"At this point, the product could probably just use a greater integration with more machine learning model tools."
"I would like a model to be available. I think Google recently released a new version of EfficientNet. It's a really good classifier, and a PyTorch implementation would be nice."
"The training of the models could be faster."
"PyTorch could make certain things more obvious. Even though it does make things like defining loss functions and calculating gradients in backward propagation clear, these concepts may confuse beginners. We find that it's kind of problematic. Despite having methods called on loss functions during backward passes, the oral documentation for beginners is quite complex."
"I've had issues with stability when I use a lot of data and try out different combinations of modeling techniques."
"There is not enough documentation about some methods and parameters. It is sometimes difficult to find information."
"On the production side of things, having more frameworks would be helpful."
Earn 20 points
OpenVINO is ranked 10th in AI Development Platforms while PyTorch is ranked 11th in AI Development Platforms with 6 reviews. OpenVINO is rated 8.6, while PyTorch is rated 8.6. The top reviewer of OpenVINO writes "Open-source, easy to integrate, and perfectly tailored to the Movidius chipset". On the other hand, the top reviewer of PyTorch writes "Offers good backward compatible and simple to use". OpenVINO is most compared with TensorFlow, Azure OpenAI, Google Cloud AI Platform, Google Vertex AI and Microsoft Azure Machine Learning Studio, whereas PyTorch is most compared with MXNet, Microsoft Azure Machine Learning Studio, Google Cloud AI Platform, Caffe and Google Vertex AI.
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