--- title: "caffe vs pytorch-metric-learning" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bvlc-caffe-vs-kevinmusgrave-pytorch-metric-learning" tools: ["bvlc-caffe", "kevinmusgrave-pytorch-metric-learning"] --- # caffe vs pytorch-metric-learning *GraphCanon updated Jul 12, 2026* ## Verdict Pick caffe when caffe is primarily C++; pytorch-metric-learning is Python; pick pytorch-metric-learning when pytorch-metric-learning 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. [pytorch-metric-learning](https://kevinmusgrave.github.io/pytorch-metric-learning/) has 6.3k stars, 659 forks, and 77 open issues, last pushed Aug 17, 2025. Figures are from public GitHub metadata via [caffe's repository](https://github.com/BVLC/caffe) and [pytorch-metric-learning's repository](https://github.com/KevinMusgrave/pytorch-metric-learning). | | [caffe](/tools/bvlc-caffe.md) | [pytorch-metric-learning](/tools/kevinmusgrave-pytorch-metric-learning.md) | | --- | --- | --- | | Tagline | Caffe: a fast open framework for deep learning. | Easily implement deep metric learning in applications using PyTorch | | Stars | 34,574 | 6,333 | | Forks | 18,458 | 659 | | Open issues | 1,209 | 77 | | Language | C++ | Python | | Adopt for | - | PyTorch Metric Learning is specifically tailored for those leveraging PyTorch and interested in applications that require distance-based learning approaches like computer vision or self-supervised learning tasks. | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | Computer Vision, Vector Databases | Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [caffe](/tools/bvlc-caffe.md) | [pytorch-metric-learning](/tools/kevinmusgrave-pytorch-metric-learning.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 710d | 327d | | Open issues (now) | 1.2k | 77 | | Owner type | Organization | User | | Full report | [trust report](/tools/bvlc-caffe/trust.md) | [trust report](/tools/kevinmusgrave-pytorch-metric-learning/trust.md) | ## Decision facts: pytorch-metric-learning - **Hosting:** library - Provides functions for implementing deep metric learning models within PyTorch. - **Pricing:** freemium - Free to use under the MIT license, with no direct costs but may require resource investment for implementation and support. - **Adopt for:** PyTorch Metric Learning is specifically tailored for those leveraging PyTorch and interested in applications that require distance-based learning approaches like computer vision or self-supervised learning tasks. ## Choose when ### Choose caffe if… - caffe is primarily C++; pytorch-metric-learning is Python. - License: caffe is Other, pytorch-metric-learning is MIT. - Tags unique to caffe: c++, machine-learning, vision. - Also covers Computer Vision, Vector Databases. ### Choose pytorch-metric-learning if… - pytorch-metric-learning is primarily Python; caffe is C++. - License: pytorch-metric-learning is MIT, caffe is Other. - Provides functions for implementing deep metric learning models within PyTorch. - Pricing: Free to use under the MIT license, with no direct costs but may require resource investment for implementation and support.. - Tags unique to pytorch-metric-learning: computer-vision, contrastive-learning, embeddings, image-retrieval. - Also covers Data & Retrieval, Model Training. - When you are working with the PyTorch framework and intend to implement deep metric learning techniques. ## 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 pytorch-metric-learning - Avoid if you are not working within the PyTorch framework and prefer to use another deep learning library as this tool is tightly integrated with PyTorch. - If your project requires a less modular setup, where customization might be more cumbersome due to pytorch-metric-learning's design towards flexibility and modularity. ## Common questions ### What is the difference between caffe and pytorch-metric-learning? caffe: Caffe: a fast open framework for deep learning.. pytorch-metric-learning: Easily implement deep metric learning in applications using PyTorch. See the comparison table for live GitHub stats and shared categories. ### When should I choose caffe over pytorch-metric-learning? Choose caffe over pytorch-metric-learning when caffe is primarily C++; pytorch-metric-learning is Python; License: caffe is Other, pytorch-metric-learning is MIT; Tags unique to caffe: c++, machine-learning, vision; Also covers Computer Vision, Vector Databases. ### When should I choose pytorch-metric-learning over caffe? Choose pytorch-metric-learning over caffe when pytorch-metric-learning is primarily Python; caffe is C++; License: pytorch-metric-learning is MIT, caffe is Other; Provides functions for implementing deep metric learning models within PyTorch; Pricing: Free to use under the MIT license, with no direct costs but may require resource investment for implementation and support.; Tags unique to pytorch-metric-learning: computer-vision, contrastive-learning, embeddings, image-retrieval; Also covers Data & Retrieval, Model Training; When you are working with the PyTorch framework and intend to implement deep metric learning techniques. ### 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 pytorch-metric-learning? Avoid if you are not working within the PyTorch framework and prefer to use another deep learning library as this tool is tightly integrated with PyTorch. If your project requires a less modular setup, where customization might be more cumbersome due to pytorch-metric-learning's design towards flexibility and modularity. ### Is caffe or pytorch-metric-learning more popular on GitHub? caffe has more GitHub stars (34,574 vs 6,333). Stars measure visibility, not whether either tool fits your constraints. ### Are caffe and pytorch-metric-learning open source? Yes - both are open-source projects on GitHub (caffe: Other, pytorch-metric-learning: MIT). ### Where can I find alternatives to caffe or pytorch-metric-learning? GraphCanon lists graph-backed alternatives at [caffe alternatives](/tools/bvlc-caffe/alternatives) and [pytorch-metric-learning alternatives](/tools/kevinmusgrave-pytorch-metric-learning/alternatives) ([caffe markdown twin](/tools/bvlc-caffe/alternatives.md), [pytorch-metric-learning markdown twin](/tools/kevinmusgrave-pytorch-metric-learning/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-kevinmusgrave-pytorch-metric-learning.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, caffe or pytorch-metric-learning? caffe: Dormant. pytorch-metric-learning: 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 pytorch-metric-learning? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [caffe trust report](/tools/bvlc-caffe/trust); [pytorch-metric-learning trust report](/tools/kevinmusgrave-pytorch-metric-learning/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/_