PyTorch vs. TensorFlow Comparison


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About Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.	About An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.
Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Not Supported On-Premises Not Supported iPhone Supported iPad Supported Android Supported Chromebook Not Supported	Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Supported On-Premises Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment	Audience Organizations interested in a powerful open source machine learning platform
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Not Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing No information available. Free Version Not Supported Free Trial Not Supported	Pricing Free Free Version Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 5.0 / 5 ease 5.0 / 5 features 5.0 / 5 design 5.0 / 5 support 5.0 / 5 Read all reviews
	Pros & Cons from Real Users Pros TensorFlow is awesome for learning and executing machine learning, machine learning models, applications, and more. It's free and open source, and easy to get started. Cons Not much I don't like about TensorFlow. It's free and open source so how can you dislike it?
Training Documentation Supported Webinars Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information PyTorch Founded: 2016 pytorch.org	Company Information TensorFlow Founded: 2015 United States www.tensorflow.org
Alternatives TensorFlow	Alternatives Gemini Enterprise Agent Platform Google
Core ML Apple	Amazon Rekognition Amazon
Create ML Apple	Amazon SageMaker Amazon
DeepSpeed Microsoft	Azure Machine Learning Microsoft
AWS Neuron Amazon Web Services View All	Kubeflow View All
Categories AI Development Supported AI/ML Model Training Supported Machine Learning Supported Neural Network Supported	Categories AI Development Supported AI/ML Model Training Supported Machine Learning Supported ML Experiment Tracking Supported ML Model Deployment Supported ML Model Management Supported Quantum Computing Supported
	Machine Learning Features Deep Learning Not Supported ML Algorithm Library Not Supported Model Training Supported Natural Language Processing (NLP) Not Supported Predictive Modeling Not Supported Statistical / Mathematical Tools Supported Templates Not Supported Visualization Supported
Integrations AI Squared Supported Amazon SageMaker Debugger Supported Amazon SageMaker Model Building Supported Apolo Supported EdgeCortix Supported Fabric for Deep Learning (FfDL) Supported Gemma Supported Gemma 2 Supported Google AI Edge Supported Label Studio Supported MLReef Supported NVIDIA FLARE Supported NVIDIA NGC Supported Runpod Supported Runyour AI Supported TensorWave Supported Thunder Compute Supported Yandex DataSphere Supported ZenML Supported Show More Integrations View All 150 Integrations	Integrations AI Squared Supported Amazon SageMaker Debugger Supported Amazon SageMaker Model Building Supported Apolo Supported EdgeCortix Supported Fabric for Deep Learning (FfDL) Supported Gemma Supported Gemma 2 Supported Google AI Edge Supported Label Studio Supported MLReef Supported NVIDIA FLARE Supported NVIDIA NGC Supported Runpod Supported Runyour AI Supported TensorWave Supported Thunder Compute Supported Yandex DataSphere Supported ZenML Supported Show More Integrations View All 193 Integrations
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