---
title: "caffe vs awesome-federated-learning"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/bvlc-caffe-vs-weimingwill-awesome-federated-learning"
tools: ["bvlc-caffe", "weimingwill-awesome-federated-learning"]
---

# caffe vs awesome-federated-learning

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick caffe when caffe is primarily C++; awesome-federated-learning is Shell; pick awesome-federated-learning when awesome-federated-learning is primarily Shell; 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-federated-learning](https://github.com/EasyFL-AI/EasyFL) has 735 stars, 98 forks, and 0 open issues, last pushed Nov 16, 2025. Figures are from public GitHub metadata via [caffe's repository](https://github.com/BVLC/caffe) and [awesome-federated-learning's repository](https://github.com/weimingwill/awesome-federated-learning).

| | [caffe](/tools/bvlc-caffe.md) | [awesome-federated-learning](/tools/weimingwill-awesome-federated-learning.md) |
| --- | --- | --- |
| Tagline | Caffe: a fast open framework for deep learning. | All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc. |
| Stars | 34,574 | 735 |
| Forks | 18,458 | 98 |
| Open issues | 1,209 | 0 |
| Language | C++ | Shell |
| Adopt for | - | - |
| Persona | - | - |
| Runtime | - | - |
| License | Other | MIT |
| 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) | [awesome-federated-learning](/tools/weimingwill-awesome-federated-learning.md) |
| --- | --- | --- |
| Maintenance | Dormant (18%) | Slowing (36%) |
| Days since push | 710d | 237d |
| Open issues (now) | 1.2k | 0 |
| Owner type | Organization | User |
| Full report | [trust report](/tools/bvlc-caffe/trust.md) | [trust report](/tools/weimingwill-awesome-federated-learning/trust.md) |

## Choose when

### Choose caffe if…

- caffe is primarily C++; awesome-federated-learning is Shell.
- License: caffe is Other, awesome-federated-learning is MIT.
- Tags unique to caffe: deep-learning, vision, machine-learning, c++.

### Choose awesome-federated-learning if…

- awesome-federated-learning is primarily Shell; caffe is C++.
- License: awesome-federated-learning is MIT, caffe is Other.
- Tags unique to awesome-federated-learning: federated-learning-framework, data-privacy, communication-efficiency, federated-learning.
- 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 awesome-federated-learning

- Last GitHub push was 237 days ago (slowing maintenance, Nov 16, 2025). Validate activity before betting a new project on awesome-federated-learning.
- 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 awesome-federated-learning?

caffe: Caffe: a fast open framework for deep learning.. awesome-federated-learning: All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.. See the comparison table for live GitHub stats and shared categories.

### When should I choose caffe over awesome-federated-learning?

Choose caffe over awesome-federated-learning when caffe is primarily C++; awesome-federated-learning is Shell; License: caffe is Other, awesome-federated-learning is MIT; Tags unique to caffe: deep-learning, vision, machine-learning, c++.

### When should I choose awesome-federated-learning over caffe?

Choose awesome-federated-learning over caffe when awesome-federated-learning is primarily Shell; caffe is C++; License: awesome-federated-learning is MIT, caffe is Other; Tags unique to awesome-federated-learning: federated-learning-framework, data-privacy, communication-efficiency, federated-learning; 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 awesome-federated-learning?

Last GitHub push was 237 days ago (slowing maintenance, Nov 16, 2025). Validate activity before betting a new project on awesome-federated-learning. 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 awesome-federated-learning more popular on GitHub?

caffe has more GitHub stars (34,574 vs 735). Stars measure visibility, not whether either tool fits your constraints.

### Are caffe and awesome-federated-learning open source?

Yes - both are open-source projects on GitHub (caffe: Other, awesome-federated-learning: MIT).

### Where can I find alternatives to caffe or awesome-federated-learning?

GraphCanon lists graph-backed alternatives at [caffe alternatives](/tools/bvlc-caffe/alternatives) and [awesome-federated-learning alternatives](/tools/weimingwill-awesome-federated-learning/alternatives) ([caffe markdown twin](/tools/bvlc-caffe/alternatives.md), [awesome-federated-learning markdown twin](/tools/weimingwill-awesome-federated-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-weimingwill-awesome-federated-learning.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, caffe or awesome-federated-learning?

caffe: Dormant. awesome-federated-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 awesome-federated-learning?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [caffe trust report](/tools/bvlc-caffe/trust); [awesome-federated-learning trust report](/tools/weimingwill-awesome-federated-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/_