--- title: "caffe vs awesome-automl-papers" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bvlc-caffe-vs-hibayesian-awesome-automl-papers" tools: ["bvlc-caffe", "hibayesian-awesome-automl-papers"] --- # caffe vs awesome-automl-papers *GraphCanon updated Jul 11, 2026* ## Verdict Pick caffe when license: caffe is Other, awesome-automl-papers is Apache-2.0; pick awesome-automl-papers when license: awesome-automl-papers is Apache-2.0, caffe is Other. [caffe](http://caffe.berkeleyvision.org/) reports 35k GitHub stars, 18k forks, and 1.2k open issues, last pushed Jul 31, 2024. [awesome-automl-papers](https://github.com/hibayesian/awesome-automl-papers) has 4.2k stars, 680 forks, and 2 open issues, last pushed Jun 11, 2024. Figures are from public GitHub metadata via [caffe's repository](https://github.com/BVLC/caffe) and [awesome-automl-papers's repository](https://github.com/hibayesian/awesome-automl-papers). | | [caffe](/tools/bvlc-caffe.md) | [awesome-automl-papers](/tools/hibayesian-awesome-automl-papers.md) | | --- | --- | --- | | Tagline | Caffe: a fast open framework for deep learning. | A curated list of automated machine learning papers, articles, tutorials, slides and projects | | Stars | 34,574 | 4,152 | | Forks | 18,458 | 680 | | Open issues | 1,209 | 2 | | Language | C++ | - | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | Computer Vision, Vector Databases | Computer Vision, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [caffe](/tools/bvlc-caffe.md) | [awesome-automl-papers](/tools/hibayesian-awesome-automl-papers.md) | | --- | --- | --- | | Days since push | 710d | 760d | | Open issues (now) | 1.2k | 2 | | Owner type | Organization | User | | Full report | [trust report](/tools/bvlc-caffe/trust.md) | [trust report](/tools/hibayesian-awesome-automl-papers/trust.md) | ## Choose when ### Choose caffe if… - License: caffe is Other, awesome-automl-papers is Apache-2.0. - Tags unique to caffe: c++, deep-learning, machine-learning, vision. - More GitHub stars (35k vs 4.2k) - visibility, not fit. ### Choose awesome-automl-papers if… - License: awesome-automl-papers is Apache-2.0, caffe is Other. - Tags unique to awesome-automl-papers: automated-feature-engineering, automl, hyperparameter-optimization, neural-architecture-search. - Leaner open-issue backlog (2). ## 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-automl-papers - Last GitHub push was 760 days ago (dormant maintenance, Jun 11, 2024). Validate activity before betting a new project on awesome-automl-papers. - 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-automl-papers? caffe: Caffe: a fast open framework for deep learning.. awesome-automl-papers: A curated list of automated machine learning papers, articles, tutorials, slides and projects. See the comparison table for live GitHub stats and shared categories. ### When should I choose caffe over awesome-automl-papers? Choose caffe over awesome-automl-papers when License: caffe is Other, awesome-automl-papers is Apache-2.0; Tags unique to caffe: c++, deep-learning, machine-learning, vision; More GitHub stars (35k vs 4.2k) - visibility, not fit. ### When should I choose awesome-automl-papers over caffe? Choose awesome-automl-papers over caffe when License: awesome-automl-papers is Apache-2.0, caffe is Other; Tags unique to awesome-automl-papers: automated-feature-engineering, automl, hyperparameter-optimization, neural-architecture-search; Leaner open-issue backlog (2). ### 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-automl-papers? Last GitHub push was 760 days ago (dormant maintenance, Jun 11, 2024). Validate activity before betting a new project on awesome-automl-papers. 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-automl-papers more popular on GitHub? caffe has more GitHub stars (34,574 vs 4,152). Stars measure visibility, not whether either tool fits your constraints. ### Are caffe and awesome-automl-papers open source? Yes - both are open-source projects on GitHub (caffe: Other, awesome-automl-papers: Apache-2.0). ### Where can I find alternatives to caffe or awesome-automl-papers? GraphCanon lists graph-backed alternatives at [caffe alternatives](/tools/bvlc-caffe/alternatives) and [awesome-automl-papers alternatives](/tools/hibayesian-awesome-automl-papers/alternatives) ([caffe markdown twin](/tools/bvlc-caffe/alternatives.md), [awesome-automl-papers markdown twin](/tools/hibayesian-awesome-automl-papers/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-hibayesian-awesome-automl-papers.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, caffe or awesome-automl-papers? caffe: Dormant. awesome-automl-papers: 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-automl-papers? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [caffe trust report](/tools/bvlc-caffe/trust); [awesome-automl-papers trust report](/tools/hibayesian-awesome-automl-papers/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/_