Side by side
MindSpore vs NVIDIA cuDNN
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
MindSpore provides a broad framework for model development, training, and deployment across hardware and environments. Review the current Transformers documentation and installation requirements before selecting it for a project.
Visit MindSpore Free plan LinuxSelf-hostedWindows
cuDNN supplies GPU-accelerated operations and graph-based fusion for deep-learning workloads. Compatibility requirements and the cuDNN 9 installation limit are important to check before adopting it.
Visit NVIDIA cuDNNThe facts
| MindSpore | NVIDIA cuDNN | |
|---|---|---|
| Free plan | Yes | Yes |
| Open source | Not published | Not published |
| Runs on | Linux, Mac, Self-hosted, Windows | Linux, Self-hosted, Windows |
| Lowest paid plan | Not published | Free or on request |
| Plans published | None | 1 |
| Maker | Not published | Not published |
| Website | mindspore.cn | developer.nvidia.com |
| On deep learning software | #20 of 35 | #16 of 35 |
MindSpore: what it does well
- Free and open source
- Supports training and inference
- Dynamic and static graph modes
- Distributed parallelism strategies
- CPU, GPU, and NPU support
What to know first
- Installation requires internet or configured internal networking
- Some Transformers capabilities remain in deprecated documentation
- Support is directed to forums and AtomGit
NVIDIA cuDNN: what it does well
- Free.
- Provides primitives for common neural-network operations.
- Integrates with a range of listed frameworks.
- Install options include pip, Docker and package managers.
What to know first
- Requires compatible OS, CUDA, driver and NVIDIA hardware.
- Only one CUDA Toolkit version of cuDNN 9 can be installed at a time.
- Use requires compliance with NVIDIA’s Software License Agreement.
Alternatives to MindSpore Alternatives to NVIDIA cuDNN The whole list