Side by side
Caffe vs DeepSpeed
Both stand on deep learning software. Which one you can start free with, which one lets you read the code, and what each costs once you pay.
Free plan LinuxMacSelf-hosted+1
Caffe brings configuration-based model setup, multiple interfaces, and CPU or GPU operation together in a free framework. Check the CUDA requirement for GPU use and the build support distinction before choosing an installation route.
Visit Caffe Free plan LinuxMacSelf-hosted
DeepSpeed combines distributed training and inference tools with integrations and monitoring options. It is free, with support and features geared toward large-scale deep learning work.
Visit DeepSpeedThe facts
| Caffe | DeepSpeed | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Linux, Mac, Self-hosted, Windows | Linux, Mac, Self-hosted |
| Lowest paid plan | Free or on request | Free or on request |
| Plans published | 1 | 1 |
| Maker | Not published | Not published |
| Website | caffe.berkeleyvision.org | deepspeed.ai |
| On deep learning software | #4 of 35 | #8 of 35 |
Caffe: what it does well
- Free under the BSD 2-Clause license
- Configuration-based model and optimization definitions
- Command-line, Python, and MATLAB interfaces
- Supports CPU-only builds and CUDA GPU operation
- Model Zoo shares model information and trained binaries
What to know first
- GPU mode requires CUDA
- CMake builds are community supported
- No free trial is listed
DeepSpeed: what it does well
- Supports mixed precision and several forms of parallelism.
- ZeRO partitions model states and gradients to reduce memory use.
- Inference supports model quantization for transformer-based PyTorch models.
- Monitor logs metrics to TensorBoard, WandB or CSV.
- Free and Apache-2.0 licensed.
What to know first
- Listed platforms are Linux, macOS and self-hosted.
- Megatron and inference features are framed around specific model workflows.
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