--- title: "caffe vs awesome-embedding-models" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bvlc-caffe-vs-hironsan-awesome-embedding-models" tools: ["bvlc-caffe", "hironsan-awesome-embedding-models"] --- # caffe vs awesome-embedding-models *GraphCanon updated Jul 11, 2026* ## Verdict Pick caffe when caffe is primarily C++; awesome-embedding-models is Jupyter Notebook; pick awesome-embedding-models when awesome-embedding-models is primarily Jupyter Notebook; caffe is C++. [caffe](http://caffe.berkeleyvision.org/) reports 35k GitHub stars, 18k forks, and 1.2k open issues, last pushed Jul 31, 2024. [awesome-embedding-models](https://github.com/Hironsan/awesome-embedding-models) has 1.8k stars, 249 forks, and 3 open issues, last pushed Apr 7, 2019. Figures are from public GitHub metadata via [caffe's repository](https://github.com/BVLC/caffe) and [awesome-embedding-models's repository](https://github.com/Hironsan/awesome-embedding-models). | | [caffe](/tools/bvlc-caffe.md) | [awesome-embedding-models](/tools/hironsan-awesome-embedding-models.md) | | --- | --- | --- | | Tagline | Caffe: a fast open framework for deep learning. | A curated list of awesome embedding models tutorials, projects and communities. | | Stars | 34,574 | 1,843 | | Forks | 18,458 | 249 | | Open issues | 1,209 | 3 | | Language | C++ | Jupyter Notebook | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | Computer Vision, Vector Databases | Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [caffe](/tools/bvlc-caffe.md) | [awesome-embedding-models](/tools/hironsan-awesome-embedding-models.md) | | --- | --- | --- | | Days since push | 710d | 2651d | | Open issues (now) | 1.2k | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/bvlc-caffe/trust.md) | [trust report](/tools/hironsan-awesome-embedding-models/trust.md) | ## Choose when ### Choose caffe if… - caffe is primarily C++; awesome-embedding-models is Jupyter Notebook. - License: caffe is Other, awesome-embedding-models is MIT. - Tags unique to caffe: c++, deep-learning, vision. - Also covers Computer Vision. ### Choose awesome-embedding-models if… - awesome-embedding-models is primarily Jupyter Notebook; caffe is C++. - License: awesome-embedding-models is MIT, caffe is Other. - Tags unique to awesome-embedding-models: awesome, embedding-models, embeddings, jupyter notebook. ## 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 awesome-embedding-models - Last GitHub push was 2652 days ago (dormant maintenance, Apr 7, 2019). Validate activity before betting a new project on awesome-embedding-models. - 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 awesome-embedding-models? caffe: Caffe: a fast open framework for deep learning.. awesome-embedding-models: A curated list of awesome embedding models tutorials, projects and communities.. See the comparison table for live GitHub stats and shared categories. ### When should I choose caffe over awesome-embedding-models? Choose caffe over awesome-embedding-models when caffe is primarily C++; awesome-embedding-models is Jupyter Notebook; License: caffe is Other, awesome-embedding-models is MIT; Tags unique to caffe: c++, deep-learning, vision; Also covers Computer Vision. ### When should I choose awesome-embedding-models over caffe? Choose awesome-embedding-models over caffe when awesome-embedding-models is primarily Jupyter Notebook; caffe is C++; License: awesome-embedding-models is MIT, caffe is Other; Tags unique to awesome-embedding-models: awesome, embedding-models, embeddings, jupyter notebook. ### 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 awesome-embedding-models? Last GitHub push was 2652 days ago (dormant maintenance, Apr 7, 2019). Validate activity before betting a new project on awesome-embedding-models. 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 awesome-embedding-models more popular on GitHub? caffe has more GitHub stars (34,574 vs 1,843). Stars measure visibility, not whether either tool fits your constraints. ### Are caffe and awesome-embedding-models open source? Yes - both are open-source projects on GitHub (caffe: Other, awesome-embedding-models: MIT). ### Where can I find alternatives to caffe or awesome-embedding-models? GraphCanon lists graph-backed alternatives at [caffe alternatives](/tools/bvlc-caffe/alternatives) and [awesome-embedding-models alternatives](/tools/hironsan-awesome-embedding-models/alternatives) ([caffe markdown twin](/tools/bvlc-caffe/alternatives.md), [awesome-embedding-models markdown twin](/tools/hironsan-awesome-embedding-models/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-hironsan-awesome-embedding-models.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, caffe or awesome-embedding-models? caffe: Dormant. awesome-embedding-models: 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 awesome-embedding-models? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [caffe trust report](/tools/bvlc-caffe/trust); [awesome-embedding-models trust report](/tools/hironsan-awesome-embedding-models/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/_