--- title: "caffe vs oneflow" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bvlc-caffe-vs-oneflow-inc-oneflow" tools: ["bvlc-caffe", "oneflow-inc-oneflow"] --- # caffe vs oneflow *GraphCanon updated Aug 3, 2026* ## Verdict Pick caffe if caffe is designed for deep learning tasks, especially those involving computer vision, and is written in C++ to ensure efficiency; pick oneflow if oneFlow is a deep learning framework built for user-friendly, scalable, and efficient performance in model training, with support via CUDA installations. [caffe](http://caffe.berkeleyvision.org/) reports 35k GitHub stars, 18k forks, and 1.5k open issues, last pushed Jul 31, 2024. [oneflow](http://www.oneflow.org) has 9.4k stars, 1.0k forks, and 644 open issues, last pushed Dec 4, 2025. Figures are from public GitHub metadata via [caffe's repository](https://github.com/BVLC/caffe) and [oneflow's repository](https://github.com/Oneflow-Inc/oneflow). | | [caffe](/tools/bvlc-caffe.md) | [oneflow](/tools/oneflow-inc-oneflow.md) | | --- | --- | --- | | Tagline | Caffe is a fast open framework for deep learning. | OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. | | Stars | 34,573 | 9,420 | | Forks | 18,443 | 1,013 | | Open issues | 1,471 | 644 | | Language | C++ | C++ | | Adopt for | Caffe is designed for deep learning tasks, especially those involving computer vision, and is written in C++ to ensure efficiency. | OneFlow is a deep learning framework built for user-friendly, scalable, and efficient performance in model training, with support via CUDA installations. | | Persona | - | - | | Runtime | - | - | | License | Caffe is available under the BSD 2-Clause license. | Apache-2.0 | | Categories | Computer Vision, Model Training | Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [caffe](/tools/bvlc-caffe.md) | [oneflow](/tools/oneflow-inc-oneflow.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 732d | 242d | | Open issues (now) | 1.5k | 644 | | Full report | [trust report](/tools/bvlc-caffe/trust.md) | [trust report](/tools/oneflow-inc-oneflow/trust.md) | ## Decision facts: caffe - **Pricing:** freemium - Free to use under open source licensing with no monetary charges. - **Adopt for:** Caffe is designed for deep learning tasks, especially those involving computer vision, and is written in C++ to ensure efficiency. - **License detail:** Caffe is available under the BSD 2-Clause license. ## Decision facts: oneflow - **Adopt for:** OneFlow is a deep learning framework built for user-friendly, scalable, and efficient performance in model training, with support via CUDA installations. ## Choose when ### Choose caffe if… - License: caffe is Other, oneflow is Apache-2.0. - Pricing: Free to use under open source licensing with no monetary charges.. - Tags unique to caffe: vision. - Also covers Computer Vision. - - You need a framework that supports high-performance convolutional networks particularly suited for image classification ### Choose oneflow if… - License: oneflow is Apache-2.0, caffe is Other. - Tags unique to oneflow: cuda, distributed, neural-networks. - OneFlow is preferable when you need a user-friendly framework for both CPU and CUDA installations, aiming to streamline the deep learning workflow. ## When NOT to use caffe - - Your primary task involves natural language processing rather than computer vision challenges, where specialized frameworks might outperform Caffe - - You seek a framework that integrates seamlessly with Python for both training and inference, as Caffe relies heavily on C++ for its core operations ## When NOT to use oneflow - Avoid OneFlow if your project requires extensive customization features not natively supported, as switching to another framework might offer better flexibility. - If the development environment lacks support for CUDA or Python3-based installation methods, consider an alternative framework that suits your hardware and software environment more closely. - OneFlow may not be ideal when working in regions with difficulty accessing external libraries due to dependency management tailored towards certain geographic locations. ## Common questions ### What is the difference between caffe and oneflow? caffe: Caffe is a fast open framework for deep learning.. oneflow: OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.. See the comparison table for live GitHub stats and shared categories. ### When should I choose caffe over oneflow? Choose caffe over oneflow when License: caffe is Other, oneflow is Apache-2.0; Pricing: Free to use under open source licensing with no monetary charges.; Tags unique to caffe: vision; Also covers Computer Vision; - You need a framework that supports high-performance convolutional networks particularly suited for image classification. ### When should I choose oneflow over caffe? Choose oneflow over caffe when License: oneflow is Apache-2.0, caffe is Other; Tags unique to oneflow: cuda, distributed, neural-networks; OneFlow is preferable when you need a user-friendly framework for both CPU and CUDA installations, aiming to streamline the deep learning workflow. ### When should I avoid caffe? - Your primary task involves natural language processing rather than computer vision challenges, where specialized frameworks might outperform Caffe - You seek a framework that integrates seamlessly with Python for both training and inference, as Caffe relies heavily on C++ for its core operations ### When should I avoid oneflow? Avoid OneFlow if your project requires extensive customization features not natively supported, as switching to another framework might offer better flexibility. If the development environment lacks support for CUDA or Python3-based installation methods, consider an alternative framework that suits your hardware and software environment more closely. OneFlow may not be ideal when working in regions with difficulty accessing external libraries due to dependency management tailored towards certain geographic locations. ### Is caffe or oneflow more popular on GitHub? caffe has more GitHub stars (34,573 vs 9,420). Stars measure visibility, not whether either tool fits your constraints. ### Are caffe and oneflow open source? Yes - both are open-source projects on GitHub (caffe: Other, oneflow: Apache-2.0). ### Where can I find alternatives to caffe or oneflow? GraphCanon lists graph-backed alternatives at [caffe alternatives](/tools/bvlc-caffe/alternatives) and [oneflow alternatives](/tools/oneflow-inc-oneflow/alternatives) ([caffe markdown twin](/tools/bvlc-caffe/alternatives.md), [oneflow markdown twin](/tools/oneflow-inc-oneflow/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/bvlc-caffe-vs-oneflow-inc-oneflow.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, caffe or oneflow? caffe: Dormant. oneflow: Slowing. 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 caffe and oneflow? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [caffe trust report](/tools/bvlc-caffe/trust); [oneflow trust report](/tools/oneflow-inc-oneflow/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bvlc-caffe`](/api/graphcanon/graph?tool=bvlc-caffe) - 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/_