Caffe vs. Keras Comparison


Caffe BAIR	Keras	+	+
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About Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Check out our web image classification demo! Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. Extensible code fosters active development. In Caffe’s first year, it has been forked by over 1,000 developers and had many significant changes contributed back. Thanks to these contributors the framework tracks the state-of-the-art in both code and models. Speed makes Caffe perfect for research experiments and industry deployment. Caffe can process over 60M images per day with a single NVIDIA K40 GPU.	About Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. Keras is the most used deep learning framework among top-5 winning teams on Kaggle. Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster. And this is how you win. Built on top of TensorFlow 2.0, Keras is an industry-strength framework that can scale to large clusters of GPUs or an entire TPU pod. It's not only possible; it's easy. Take advantage of the full deployment capabilities of the TensorFlow platform. You can export Keras models to JavaScript to run directly in the browser, to TF Lite to run on iOS, Android, and embedded devices. It's also easy to serve Keras models as via a web API.
Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Supported On-Premises Not Supported iPhone Supported iPad Supported Android Supported Chromebook Not Supported
Audience Anyone looking for an open-source deep learning framework with expression, speed and modularity	Audience Developers interested in an deep learning API solution to minimize the number of user actions required for common use cases
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 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 Supported Free Trial Not Supported	Pricing No information available. Free Version Not 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 Read all reviews
	Pros & Cons from Real Users Pros I mostly code in Python, so using Keras for my deep learning needs wasn't too hard to get used to, given the abundance of documentation and ease of writing modular code with its API. Cons Keras only has high level APIs, unlike Tensorflow, which has both high and low level support.
Training Documentation Supported Webinars Not 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 BAIR United States caffe.berkeleyvision.org	Company Information Keras United States keras.io
Alternatives MXNet The Apache Software Foundation	Alternatives TensorFlow
DeepSpeed Microsoft	PyTorch
Gemini Enterprise Agent Platform Google	AWS Deep Learning AMIs Amazon
PyTorch	AutoKeras
AWS Deep Learning AMIs Amazon View All	Deeplearning4j View All
Categories AI Development Supported AI/ML Model Training Supported Deep Learning Supported Neural Network Supported	Categories Deep Learning Supported Neural Network Supported
Deep Learning Features Convolutional Neural Networks Not Supported Document Classification Supported Image Segmentation Not Supported ML Algorithm Library Not Supported Model Training Not Supported Neural Network Modeling Not Supported Self-Learning Not Supported Visualization Supported	Deep Learning Features Convolutional Neural Networks Supported Document Classification Not Supported Image Segmentation Not Supported ML Algorithm Library Not Supported Model Training Not Supported Neural Network Modeling Not Supported Self-Learning Not Supported Visualization Supported
Integrations Lambda Supported OpenVINO Supported Polyaxon Supported Cameralyze Not Supported Comet LLM Not Supported Fabric for Deep Learning (FfDL) Supported Flower Not Supported Gemma 3 Not Supported Graphcore Not Supported Jovian Not Supported Radicalbit Not Supported RazorThink Not Supported RunCode Not Supported StreamFlux Not Supported Weights & Biases Not Supported Zebra by Mipsology Supported Zorro Not Supported Show More Integrations View All 13 Integrations	Integrations Lambda Supported OpenVINO Supported Polyaxon Supported Cameralyze Supported Comet LLM Supported Fabric for Deep Learning (FfDL) Not Supported Flower Supported Gemma 3 Supported Graphcore Supported Jovian Supported Radicalbit Supported RazorThink Supported RunCode Supported StreamFlux Supported Weights & Biases Supported Zebra by Mipsology Not Supported Zorro Supported Show More Integrations View All 51 Integrations
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