--- title: "caffe vs determined" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bvlc-caffe-vs-determined-ai-determined" tools: ["bvlc-caffe", "determined-ai-determined"] --- # caffe vs determined *GraphCanon updated Aug 4, 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 determined if determined is an open-source machine learning platform that simplifies distributed training and hyperparameter tuning for PyTorch and TensorFlow applications. [caffe](http://caffe.berkeleyvision.org/) reports 35k GitHub stars, 18k forks, and 1.5k open issues, last pushed Jul 31, 2024. [determined](https://determined.ai) has 3.2k stars, 373 forks, and 108 open issues, last pushed Mar 20, 2025. Figures are from public GitHub metadata via [caffe's repository](https://github.com/BVLC/caffe) and [determined's repository](https://github.com/determined-ai/determined). | | [caffe](/tools/bvlc-caffe.md) | [determined](/tools/determined-ai-determined.md) | | --- | --- | --- | | Tagline | Caffe is a fast open framework for deep learning. | An open-source machine learning platform for distributed training and resource management. | | Stars | 34,573 | 3,227 | | Forks | 18,443 | 373 | | Open issues | 1,471 | 108 | | Language | C++ | Go | | Adopt for | Caffe is designed for deep learning tasks, especially those involving computer vision, and is written in C++ to ensure efficiency. | Determined is an open-source machine learning platform that simplifies distributed training and hyperparameter tuning for PyTorch and TensorFlow applications. | | Persona | - | - | | Runtime | - | - | | License | Caffe is available under the BSD 2-Clause license. | Apache-2.0 | | Categories | Computer Vision, Model Training | Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [caffe](/tools/bvlc-caffe.md) | [determined](/tools/determined-ai-determined.md) | | --- | --- | --- | | Days since push | 732d | 501d | | Open issues (now) | 1.5k | 108 | | Full report | [trust report](/tools/bvlc-caffe/trust.md) | [trust report](/tools/determined-ai-determined/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: determined - **Pricing:** freemium - The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here. - **Requirements:** Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via `det deploy`. - **Adopt for:** Determined is an open-source machine learning platform that simplifies distributed training and hyperparameter tuning for PyTorch and TensorFlow applications. - **License detail:** Apache-2.0 ## Choose when ### Choose caffe if… - caffe is primarily C++; determined is Go. - License: caffe is Other, determined is Apache-2.0. - Pricing: Free to use under open source licensing with no monetary charges.. - Tags unique to caffe: machine-learning, vision. - Also covers Computer Vision. - - You need a framework that supports high-performance convolutional networks particularly suited for image classification ### Choose determined if… - determined is primarily Go; caffe is C++. - License: determined is Apache-2.0, caffe is Other. - Pricing: The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here.. - Requirements: Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via `det deploy`.. - Tags unique to determined: data-science, distributed-training, hyperparameter-optimization, ml-infrastructure. - Also covers Evaluation & Observability. - You require a streamlined solution for distributed model training, particularly if you are working with PyTorch or TensorFlow frameworks. ## 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 determined - Seeking a platform that supports more machine learning frameworks beyond PyTorch and TensorFlow. - Your current stack does not include any of the supported infrastructures like Kubernetes or cloud services where Determined can be deployed. ## Common questions ### What is the difference between caffe and determined? caffe: Caffe is a fast open framework for deep learning.. determined: An open-source machine learning platform for distributed training and resource management.. See the comparison table for live GitHub stats and shared categories. ### When should I choose caffe over determined? Choose caffe over determined when caffe is primarily C++; determined is Go; License: caffe is Other, determined is Apache-2.0; Pricing: Free to use under open source licensing with no monetary charges.; Tags unique to caffe: machine-learning, vision; Also covers Computer Vision; - You need a framework that supports high-performance convolutional networks particularly suited for image classification. ### When should I choose determined over caffe? Choose determined over caffe when determined is primarily Go; caffe is C++; License: determined is Apache-2.0, caffe is Other; Pricing: The open-source version under Apache License is free to use. Additional enterprise features may incur costs, though specific pricing details are not provided here.; Requirements: Installation involves using 'pip' for the CLI and subsequent cluster deployment steps via `det deploy`.; Tags unique to determined: data-science, distributed-training, hyperparameter-optimization, ml-infrastructure; Also covers Evaluation & Observability; You require a streamlined solution for distributed model training, particularly if you are working with PyTorch or TensorFlow frameworks. ### 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 determined? Seeking a platform that supports more machine learning frameworks beyond PyTorch and TensorFlow. Your current stack does not include any of the supported infrastructures like Kubernetes or cloud services where Determined can be deployed. ### Is caffe or determined more popular on GitHub? caffe has more GitHub stars (34,573 vs 3,227). Stars measure visibility, not whether either tool fits your constraints. ### Are caffe and determined open source? Yes - both are open-source projects on GitHub (caffe: Other, determined: Apache-2.0). ### Where can I find alternatives to caffe or determined? GraphCanon lists graph-backed alternatives at [caffe alternatives](/tools/bvlc-caffe/alternatives) and [determined alternatives](/tools/determined-ai-determined/alternatives) ([caffe markdown twin](/tools/bvlc-caffe/alternatives.md), [determined markdown twin](/tools/determined-ai-determined/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-determined-ai-determined.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, caffe or determined? caffe: Dormant. determined: 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 caffe and determined? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [caffe trust report](/tools/bvlc-caffe/trust); [determined trust report](/tools/determined-ai-determined/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/_