Caffe vs. DeepSpeed Comparison


Caffe BAIR	DeepSpeed Microsoft	+	+
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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 DeepSpeed is an open source deep learning optimization library for PyTorch. It's designed to reduce computing power and memory use, and to train large distributed models with better parallelism on existing computer hardware. DeepSpeed is optimized for low latency, high throughput training. DeepSpeed can train DL models with over a hundred billion parameters on the current generation of GPU clusters. It can also train up to 13 billion parameters in a single GPU. DeepSpeed is developed by Microsoft and aims to offer distributed training for large-scale models. It's built on top of PyTorch, which specializes in data parallelism.
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 Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Anyone looking for an open-source deep learning framework with expression, speed and modularity	Audience Deep learning model developers
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 Not Supported
API Offers API Supported	API Offers API Not 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 Free Open source 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 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

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 Microsoft Founded: 1975 United States www.deepspeed.ai/
Alternatives MXNet The Apache Software Foundation	Alternatives Horovod
DeepSpeed Microsoft	Unsloth
Gemini Enterprise Agent Platform Google	GPT-NeoX EleutherAI
PyTorch	AWS Neuron Amazon Web Services
NVIDIA GPU-Optimized AMI Amazon View All	Amazon SageMaker Model Training Amazon View All
Categories AI Development Supported AI/ML Model Training Supported Deep Learning Supported Neural Network Supported	Categories AI Development Supported AI/ML Model Training Supported Deep Learning 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
Integrations AWS Elastic Fabric Adapter (EFA) Supported AWS Marketplace Supported Amazon Web Services (AWS) Supported Axolotl Not Supported Cake AI Not Supported Comet LLM Not Supported Docker Supported Fabric for Deep Learning (FfDL) Supported Lambda Supported NVIDIA DIGITS Supported Nurix Not Supported OpenVINO Supported Polyaxon Supported Pop!_OS Supported PyTorch Not Supported Python Not Supported Zebra by Mipsology Supported Show More Integrations View All 13 Integrations	Integrations AWS Elastic Fabric Adapter (EFA) Not Supported AWS Marketplace Not Supported Amazon Web Services (AWS) Not Supported Axolotl Supported Cake AI Supported Comet LLM Supported Docker Not Supported Fabric for Deep Learning (FfDL) Not Supported Lambda Not Supported NVIDIA DIGITS Not Supported Nurix Supported OpenVINO Not Supported Polyaxon Not Supported Pop!_OS Not Supported PyTorch Supported Python Supported Zebra by Mipsology Not Supported Show More Integrations View All 6 Integrations
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