Chainer vs ONNX Runtime
Chainer
chainer.orgONNX Runtime
onnxruntime.aiSide by side
| Figure | Chainer | ONNX Runtime |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| iOS | — | Yes |
| Android | — | Yes |
| API | Yes | — |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 1 |
| Spec score · Deep Learning Software | 7.9 (#14) | 8.4 (#6) |
| Integrations | The v7 release announcement says ONNX-Chainer is integrated into Chainer and that most Chainer features, including ChainerMN, are compatible with ChainerX ndarray. | 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. |
| Platforms | The recommended environments are 64-bit Ubuntu 14.04/16.04 LTS and CentOS 7; the documentation says it cannot guarantee operation on Windows or macOS. | The site says ONNX Runtime runs on Linux, Windows, Mac, iOS, Android, and web browsers. |
Plans
In their own words
ONNX Runtime
ONNX Runtime is a free engine for machine-learning inference and training within existing technology stacks. It can run models from frameworks including PyTorch, TensorFlow/Keras, TFLite, and scikit-learn. For inference, it optimizes latency, throughput, memory use, and binary size through graph transformations, accelerator-aware partitioning, and optimized computation kernels. Its Execution Providers connect ONNX models to hardware acceleration libraries for CPUs, GPUs, FPGAs, and specialized NPUs. Listed options include NVIDIA CUDA and TensorRT, Intel OpenVINO, DirectML, Qualcomm QNN, Android NNAPI, Apple CoreML, and WebGPU. Deployment spans cloud servers, edge and mobile devices, and browsers; its web runtime supports browser models and its mobile runtime supports Android and iOS. Supported languages include Python, C#, C++, Java, JavaScript, and Rust. Developers can create smaller web or mobile packages by including only the operators and opsets their models need. The open-source runtime is available on Android, iOS, Linux, macOS, self-hosted environments, web, and Windows.