--- title: "DeepLearningExamples vs Forward" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nvidia-deeplearningexamples-vs-tencent-forward" tools: ["nvidia-deeplearningexamples", "tencent-forward"] --- # DeepLearningExamples vs Forward *GraphCanon updated Aug 17, 2026* ## Verdict Pick DeepLearningExamples if curated facts for DeepLearningExamples, tailored to its unique features and offerings; pick Forward if forward is an NVIDIA GPU-based high-performance deep learning inference library that converts popular framework models directly into TensorRT for optimized inference. [DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples) reports 15k GitHub stars, 3.4k forks, and 321 open issues, last pushed Aug 12, 2024. [Forward](https://github.com/Tencent/Forward) has 556 stars, 63 forks, and 0 open issues, last pushed Jan 29, 2022. Figures are from public GitHub metadata via [DeepLearningExamples's repository](https://github.com/NVIDIA/DeepLearningExamples) and [Forward's repository](https://github.com/Tencent/Forward). | | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | [Forward](/tools/tencent-forward.md) | | --- | --- | --- | | Tagline | State-of-the-Art Deep Learning scripts for various applications | A library for high performance deep learning inference on NVIDIA GPUs | | Stars | 14,844 | 556 | | Forks | 3,408 | 63 | | Open issues | 321 | 0 | | Language | Jupyter Notebook | C++ | | Adopt for | Curated facts for DeepLearningExamples, tailored to its unique features and offerings. | Forward is an NVIDIA GPU-based high-performance deep learning inference library that converts popular framework models directly into TensorRT for optimized inference. | | Persona | - | - | | Runtime | - | - | | License | - | Other license type - specific terms not detailed here; consult repository for details on licensing implications and permissiveness of use and distribution. | | Categories | Inference & Serving, Model Training | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepLearningExamples](/tools/nvidia-deeplearningexamples.md) | [Forward](/tools/tencent-forward.md) | | --- | --- | --- | | Days since push | 734d | 1647d | | Open issues (now) | 321 | 0 | | Stars delta | +14 (30d) | Unknown | | Open issues delta | -1 (30d) | Unknown | | Full report | [trust report](/tools/nvidia-deeplearningexamples/trust.md) | [trust report](/tools/tencent-forward/trust.md) | ## Decision facts: DeepLearningExamples - **Adopt for:** Curated facts for DeepLearningExamples, tailored to its unique features and offerings. ## Decision facts: Forward - **Adopt for:** Forward is an NVIDIA GPU-based high-performance deep learning inference library that converts popular framework models directly into TensorRT for optimized inference. - **License detail:** Other license type - specific terms not detailed here; consult repository for details on licensing implications and permissiveness of use and distribution. ## Choose when ### Choose DeepLearningExamples if… - DeepLearningExamples is primarily Jupyter Notebook; Forward is C++. - Tags unique to DeepLearningExamples: computer-vision, drug-discovery, forecasting, large language models. - Also covers Model Training. - The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance. ### Choose Forward if… - Forward is primarily C++; DeepLearningExamples is Jupyter Notebook. - Tags unique to Forward: cuda, forward, gpu, inference. - When you need to quickly integrate TensorFlow, PyTorch, Keras, or ONNX models on NVIDIA GPUs for inference and require minimal conversion effort. ## 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 Forward - If your project requires model serving or inference on CPU-only environments, as Forward is optimized for NVIDIA GPUs. - For users who need extensive customization beyond the supported models (TensorFlow, PyTorch, Keras, ONNX) as expanding support necessitates additional engineering effort. ## Common questions ### What is the difference between DeepLearningExamples and Forward? DeepLearningExamples: State-of-the-Art Deep Learning scripts for various applications. Forward: A library for high performance deep learning inference on NVIDIA GPUs. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepLearningExamples over Forward? Choose DeepLearningExamples over Forward when DeepLearningExamples is primarily Jupyter Notebook; Forward is C++; Tags unique to DeepLearningExamples: computer-vision, drug-discovery, forecasting, large language models; Also covers Model Training; 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 Forward over DeepLearningExamples? Choose Forward over DeepLearningExamples when Forward is primarily C++; DeepLearningExamples is Jupyter Notebook; Tags unique to Forward: cuda, forward, gpu, inference; When you need to quickly integrate TensorFlow, PyTorch, Keras, or ONNX models on NVIDIA GPUs for inference and require minimal conversion effort. ### 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 Forward? If your project requires model serving or inference on CPU-only environments, as Forward is optimized for NVIDIA GPUs. For users who need extensive customization beyond the supported models (TensorFlow, PyTorch, Keras, ONNX) as expanding support necessitates additional engineering effort. ### Is DeepLearningExamples or Forward more popular on GitHub? DeepLearningExamples has more GitHub stars (14,844 vs 556). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepLearningExamples and Forward open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to DeepLearningExamples or Forward? GraphCanon lists graph-backed alternatives at [DeepLearningExamples alternatives](/tools/nvidia-deeplearningexamples/alternatives) and [Forward alternatives](/tools/tencent-forward/alternatives) ([DeepLearningExamples markdown twin](/tools/nvidia-deeplearningexamples/alternatives.md), [Forward markdown twin](/tools/tencent-forward/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-tencent-forward.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepLearningExamples or Forward? DeepLearningExamples: Dormant. Forward: Dormant. 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 Forward? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepLearningExamples trust report](/tools/nvidia-deeplearningexamples/trust); [Forward trust report](/tools/tencent-forward/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/_