MLX provides an array computing framework designed for Apple silicon devices.
Open source
24 alternativesPaddlePaddle
PaddlePaddle provides a deep learning framework for training models across devices and platforms.
About PaddlePaddle
PaddlePaddle is an open-source deep learning framework for single-machine and distributed training and cross-platform deployment. It includes core framework code, model libraries, development kits, and related tools and components.
It supports unified dynamic and static graphs with automatic parallelism, combined training and inference for large models, and routines for scientific computing such as high-order differentiation, complex-number operations and Fourier transforms. The source notes version 3.3 as the latest release and documentation in English and Chinese.
Key features
- Single-machine and distributed training for deep learning models
- Cross-platform deployment of trained models
- Unified dynamic and static graphs with automatic parallelism
- Shared framework for large-model training and inference
- High-order differentiation for scientific computing tasks
- Support for multiple chip types through standardized interfaces
Best for: Developers who train and deploy deep learning models, including large models and scientific computing workloads, across different hardware.
Good for
- Open-source code available through a public repository
- Same framework covers training and inference for large-model workflows
- Documentation available in English and Chinese
PaddlePaddle at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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PaddlePaddle FAQ
What is the latest release noted in the source?
Version 3.3 is listed as the latest PaddlePaddle release.
How is PaddlePaddle installed?
Stable and nightly releases are offered, with details described under Quick Install.
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