DeepSpeed
6.0#19 in deep learning softwareFree planFree planLinuxmacOSSelf-hosted
VisitDeepSpeed vs ONNX Runtime
ONNX Runtime
7.2#4 in deep learning softwareFree planFree planAndroidiOSWebLinux
VisitWhat both publish
| Fact | DeepSpeed | ONNX Runtime |
|---|---|---|
| Integrations | The site lists integrations with Hugging Face Transformers, Accelerate, PyTorch Lightning and MosaicML. | The ecosystem documentation lists integrations with Azure Machine Learning, Azure Custom Vision, Azure SQL Edge, Azure Synapse Analytics, ML.NET, and NVIDIA Triton Inference Server. |
| Purpose | DeepSpeed is a deep learning optimization library for distributed model training and inference. | ONNX Runtime is a production-grade engine for accelerating machine-learning training and inference in existing technology stacks. |
| Support | The GitHub repository says DeepSpeed holds public office hours on the last Tuesday of each month. | Documentation questions are directed to issue filing, and the project invites users to report bugs, suggest features, and submit pull requests on GitHub. |
| Training | Its training features include mixed precision, data, model and pipeline parallelism, and the ZeRO optimizer. | ONNX Runtime supports on-device training and says it can reduce costs for large-model training. |
DeepSpeed plans
- DeepSpeedFree
ONNX Runtime plans
- Open sourceFree
Pick DeepSpeed if…
DeepSpeed is aimed at deep-learning researchers and practitioners working on large-scale training and inference. It may suit Python users seeking distributed training, model parallelism or inference optimization.
Pick ONNX Runtime if…
ONNX Runtime suits developers deploying machine-learning models across varied devices and hardware accelerators. It may also suit teams seeking local training or browser and mobile inference.