--- title: "DeepLearningExamples vs mmengine" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nvidia-deeplearningexamples-vs-open-mmlab-mmengine" tools: ["nvidia-deeplearningexamples", "open-mmlab-mmengine"] --- # DeepLearningExamples vs mmengine *GraphCanon updated Aug 17, 2026* ## Verdict Pick DeepLearningExamples if curated facts for DeepLearningExamples, tailored to its unique features and offerings; pick mmengine if mMEngine, part of OpenMMLab, serves as a foundational library for training deep learning models with PyTorch in Python. [DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples) reports 15k GitHub stars, 3.4k forks, and 321 open issues, last pushed Aug 12, 2024. [mmengine](https://mmengine.readthedocs.io/) has 1.5k stars, 455 forks, and 260 open issues, last pushed Jul 13, 2026. Figures are from public GitHub metadata via [DeepLearningExamples's repository](https://github.com/NVIDIA/DeepLearningExamples) and [mmengine's repository](https://github.com/open-mmlab/mmengine). | | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | [mmengine](/tools/open-mmlab-mmengine.md) | | --- | --- | --- | | Tagline | State-of-the-Art Deep Learning scripts for various applications | OpenMMLab Foundational Library for Training Deep Learning Models | | Stars | 14,844 | 1,482 | | Forks | 3,408 | 455 | | Open issues | 321 | 260 | | Language | Jupyter Notebook | Python | | Adopt for | Curated facts for DeepLearningExamples, tailored to its unique features and offerings. | MMEngine, part of OpenMMLab, serves as a foundational library for training deep learning models with PyTorch in Python. | | Persona | - | - | | Runtime | - | - | | License | - | MMEngine is distributed under the Apache 2.0 License. | | Categories | Inference & Serving, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | [mmengine](/tools/open-mmlab-mmengine.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 734d | 18d | | Open issues (now) | 321 | 260 | | Stars delta | +14 (30d) | Unknown | | Open issues delta | -1 (30d) | Unknown | | Full report | [trust report](/tools/nvidia-deeplearningexamples/trust.md) | [trust report](/tools/open-mmlab-mmengine/trust.md) | ## Decision facts: DeepLearningExamples - **Adopt for:** Curated facts for DeepLearningExamples, tailored to its unique features and offerings. ## Decision facts: mmengine - **Pricing:** freemium - The core functionality for model training offered through MMEngine is accessible without cost due to its licensing terms (Apache 2.0). - **Adopt for:** MMEngine, part of OpenMMLab, serves as a foundational library for training deep learning models with PyTorch in Python. - **License detail:** MMEngine is distributed under the Apache 2.0 License. ## Choose when ### Choose DeepLearningExamples if… - DeepLearningExamples is primarily Jupyter Notebook; mmengine is Python. - Tags unique to DeepLearningExamples: drug-discovery, forecasting, large language models, mxnet. - Also covers Inference & Serving. - The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance. ### Choose mmengine if… - mmengine is primarily Python; DeepLearningExamples is Jupyter Notebook. - Pricing: The core functionality for model training offered through MMEngine is accessible without cost due to its licensing terms (Apache 2.0).. - Tags unique to mmengine: ai, machine-learning, python, pytorch. - - Use MMEngine when you are leveraging PyTorch and require a solid foundation for your deep learning model training processes. ## When NOT to use DeepLearningExamples - Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores. - If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n ## When NOT to use mmengine - - Avoid using MMEngine if your project requires a Python version outside of the supported range (e.g., Python 3.12+). - - If you are working with frameworks other than PyTorch, MMEngine might not be suitable as it is specifically optimized for PyTorch support. - - Consider an alternative if you are looking for more flexibility beyond the specific use cases catered to by OpenMMLab and do not want to be tied into their ecosystem. ## Common questions ### What is the difference between DeepLearningExamples and mmengine? DeepLearningExamples: State-of-the-Art Deep Learning scripts for various applications. mmengine: OpenMMLab Foundational Library for Training Deep Learning Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepLearningExamples over mmengine? Choose DeepLearningExamples over mmengine when DeepLearningExamples is primarily Jupyter Notebook; mmengine is Python; Tags unique to DeepLearningExamples: drug-discovery, forecasting, large language models, mxnet; Also covers Inference & Serving; The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance. ### When should I choose mmengine over DeepLearningExamples? Choose mmengine over DeepLearningExamples when mmengine is primarily Python; DeepLearningExamples is Jupyter Notebook; Pricing: The core functionality for model training offered through MMEngine is accessible without cost due to its licensing terms (Apache 2.0).; Tags unique to mmengine: ai, machine-learning, python, pytorch; - Use MMEngine when you are leveraging PyTorch and require a solid foundation for your deep learning model training processes. ### When should I avoid DeepLearningExamples? Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores. If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n ### When should I avoid mmengine? - Avoid using MMEngine if your project requires a Python version outside of the supported range (e.g., Python 3.12+). - If you are working with frameworks other than PyTorch, MMEngine might not be suitable as it is specifically optimized for PyTorch support. - Consider an alternative if you are looking for more flexibility beyond the specific use cases catered to by OpenMMLab and do not want to be tied into their ecosystem. ### Is DeepLearningExamples or mmengine more popular on GitHub? DeepLearningExamples has more GitHub stars (14,844 vs 1,482). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepLearningExamples and mmengine open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to DeepLearningExamples or mmengine? GraphCanon lists graph-backed alternatives at [DeepLearningExamples alternatives](/tools/nvidia-deeplearningexamples/alternatives) and [mmengine alternatives](/tools/open-mmlab-mmengine/alternatives) ([DeepLearningExamples markdown twin](/tools/nvidia-deeplearningexamples/alternatives.md), [mmengine markdown twin](/tools/open-mmlab-mmengine/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/nvidia-deeplearningexamples-vs-open-mmlab-mmengine.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepLearningExamples or mmengine? DeepLearningExamples: Dormant. mmengine: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for DeepLearningExamples and mmengine? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepLearningExamples trust report](/tools/nvidia-deeplearningexamples/trust); [mmengine trust report](/tools/open-mmlab-mmengine/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nvidia-deeplearningexamples`](/api/graphcanon/graph?tool=nvidia-deeplearningexamples) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_