Caffe vs MegEngine
Caffe
caffe.berkeleyvision.orgMegEngine
megengine.org.cnSide by side
| Figure | Caffe | MegEngine |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · Deep Learning Software | 8.1 (#9) | 7.9 (#15) |
| Purpose | Caffe is a deep learning framework developed by Berkeley AI Research and community contributors. | MegEngine is a fast, scalable deep learning framework with automatic differentiation. |
| Support | The site directs usage and installation questions to the caffe-users group and bug reports to GitHub Issues. | The project lists GitHub issues, a forum, QQ group and [email protected] for contact. |
Plans
In their own words
Caffe
Caffe has no write-up on Specifiction yet; its figures are above.
MegEngine
MegEngine is a free, open-source deep learning framework for developing and deploying models, with automatic differentiation. It uses one model for training and inference, including quantization and dynamic shapes. The project says enabling DTR can reduce GPU memory use to one-third of the original. Inference is supported across x86, Arm, CUDA, and ROCm; GPU use requires compatible device drivers. Python packages are listed for 64-bit Linux and Windows, macOS 10.14 or later, and Android 7 or later, though macOS and Android installations are CPU-only. The installation guide specifies Python 3.6–3.9. MegEngine Lite supplies C/C++, Rust, and Python runtimes for deployment. MgeConvert handles conversion between MegEngine and third-party model formats, MegFile provides Python file interfaces for S3, HTTP, and local files, and MegFlow is a streaming computation framework for AI applications. Tutorials address beginners and advanced developers. Support options include GitHub issues, a forum, a QQ group, and email.