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Mmdeploy
MMDeploy provides a model deployment framework from the OpenMMLab project.

About Mmdeploy
MMDeploy is an open-source deep learning model deployment toolset from the OpenMMLab project. It converts and runs models built with OpenMMLab codebases, including mmpretrain, mmdet, mmseg, mmocr, mmpose, and mmaction2, across several inference backends.
The project publishes a device, platform, and backend support matrix covering Linux, Windows, macOS, Android, and several hardware targets. Support depends on the specific combination, and some combinations are not listed. Version 1.x is the maintained line for new features, and users should align MMDeploy's version with their OpenMMLab 2.0 codebases. The 0.x branch is slated for deprecation. Pricing is unknown, and the project is released under the Apache 2.0 license.
Key features
- Deployment support for models from multiple OpenMMLab codebases, including mmdet and mmseg
- Multiple inference backends, including ONNX Runtime, TensorRT, OpenVINO, and ncnn
- Device and platform matrix spanning Linux, Windows, macOS, Android, and embedded hardware
- Extensible C/C++ SDK with customizable Transform, Net, and Module components
- Guides for model conversion, configuration, profiling, and quantization
- Released under the Apache 2.0 open-source license
- Part of the OpenMMLab project, with a published list of supported codebases and models
- Broad backend and hardware coverage listed in its support matrix
- Support varies by device, platform, and backend combination, and some combinations are not listed
- Version 1.x is aligned with OpenMMLab 2.0, so users must match versions
- The 0.x branch will be deprecated, and new features will only be added to 1.x
Mmdeploy at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
Mmdeploy alternatives
Tools and sites you could use instead, ranked by how closely they match.
Merlin supports machine learning model management, deployment, and serving in Kubernetes environments.
Eurybia tracks model drift and validates data during machine learning model deployment.
Model deployment for AI applications is supported by nndeploy, a framework described as easy to use and high performance.
Cog packages machine learning models into containers to support deployment across environments.
ONNX-MLIR compiles ONNX models using MLIR compiler infrastructure for model deployment workflows.
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Mmdeploy FAQ
Which OpenMMLab codebases does MMDeploy support?
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Which version should new users use?
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