--- title: "caffe vs hub" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bvlc-caffe-vs-tensorflow-hub" tools: ["bvlc-caffe", "tensorflow-hub"] --- # caffe vs hub *GraphCanon updated Jul 12, 2026* ## Verdict Pick caffe when caffe is primarily C++; hub is Python; pick hub when hub is primarily Python; caffe is C++. [caffe](http://caffe.berkeleyvision.org/) reports 35k GitHub stars, 18k forks, and 1.2k open issues, last pushed Jul 31, 2024. [hub](https://tensorflow.org/hub) has 3.5k stars, 1.6k forks, and 14 open issues, last pushed Jan 17, 2025. Figures are from public GitHub metadata via [caffe's repository](https://github.com/BVLC/caffe) and [hub's repository](https://github.com/tensorflow/hub). | | [caffe](/tools/bvlc-caffe.md) | [hub](/tools/tensorflow-hub.md) | | --- | --- | --- | | Tagline | Caffe: a fast open framework for deep learning. | A library for transfer learning by reusing parts of TensorFlow models. | | Stars | 34,574 | 3,521 | | Forks | 18,458 | 1,644 | | Open issues | 1,209 | 14 | | Language | C++ | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | Vector Databases, Computer Vision | Model Training, Vector Databases, Computer Vision | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [caffe](/tools/bvlc-caffe.md) | [hub](/tools/tensorflow-hub.md) | | --- | --- | --- | | Days since push | 710d | 539d | | Open issues (now) | 1.2k | 14 | | Full report | [trust report](/tools/bvlc-caffe/trust.md) | [trust report](/tools/tensorflow-hub/trust.md) | ## Choose when ### Choose caffe if… - caffe is primarily C++; hub is Python. - License: caffe is Other, hub is Apache-2.0. - Tags unique to caffe: deep-learning, vision, c++. ### Choose hub if… - hub is primarily Python; caffe is C++. - License: hub is Apache-2.0, caffe is Other. - Tags unique to hub: ml, embeddings, python, image-classification. - Also covers Model Training. ## When NOT to use caffe - Last GitHub push was 710 days ago (dormant maintenance, Jul 31, 2024). Validate activity before betting a new project on caffe. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## When NOT to use hub - Last GitHub push was 540 days ago (dormant maintenance, Jan 17, 2025). Validate activity before betting a new project on hub. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between caffe and hub? caffe: Caffe: a fast open framework for deep learning.. hub: A library for transfer learning by reusing parts of TensorFlow models.. See the comparison table for live GitHub stats and shared categories. ### When should I choose caffe over hub? Choose caffe over hub when caffe is primarily C++; hub is Python; License: caffe is Other, hub is Apache-2.0; Tags unique to caffe: deep-learning, vision, c++. ### When should I choose hub over caffe? Choose hub over caffe when hub is primarily Python; caffe is C++; License: hub is Apache-2.0, caffe is Other; Tags unique to hub: ml, embeddings, python, image-classification; Also covers Model Training. ### When should I avoid caffe? Last GitHub push was 710 days ago (dormant maintenance, Jul 31, 2024). Validate activity before betting a new project on caffe. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### When should I avoid hub? Last GitHub push was 540 days ago (dormant maintenance, Jan 17, 2025). Validate activity before betting a new project on hub. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is caffe or hub more popular on GitHub? caffe has more GitHub stars (34,574 vs 3,521). Stars measure visibility, not whether either tool fits your constraints. ### Are caffe and hub open source? Yes - both are open-source projects on GitHub (caffe: Other, hub: Apache-2.0). ### Where can I find alternatives to caffe or hub? GraphCanon lists graph-backed alternatives at [caffe alternatives](/tools/bvlc-caffe/alternatives) and [hub alternatives](/tools/tensorflow-hub/alternatives) ([caffe markdown twin](/tools/bvlc-caffe/alternatives.md), [hub markdown twin](/tools/tensorflow-hub/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-tensorflow-hub.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, caffe or hub? caffe: Dormant. hub: 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 hub? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [caffe trust report](/tools/bvlc-caffe/trust); [hub trust report](/tools/tensorflow-hub/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/_