Comparison
caffe vs lightly
Verdict
Pick caffe when caffe is primarily C++; lightly is Python; pick lightly when lightly is primarily Python; caffe is C++.
Markdown twin · caffe alternatives · lightly alternatives
GraphCanon updated today
Trust & integrity
| Signal | caffe | lightly |
|---|---|---|
| Maintenance | Dormant (710d since push) As of today · github_public_v1 | Very active (1d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- caffe
- Caffe: a fast open framework for deep learning.
- lightly
- A python library for self-supervised learning on images.
Stars
- caffe
- 35k
- lightly
- 3.8k
Forks
- caffe
- 18k
- lightly
- 339
Open issues
- caffe
- 1.2k
- lightly
- 92
Language
- caffe
- C++
- lightly
- Python
Adopt for
- caffe
- -
- lightly
- -
Persona
- caffe
- -
- lightly
- -
Runtime
- caffe
- -
- lightly
- -
License
- caffe
- Other
- lightly
- MIT
Last pushed
- caffe
- Jul 31, 2024
- lightly
- Jul 9, 2026
Categories
- caffe
- Vector Databases, Computer Vision
- lightly
- Vector Databases, Model Training, Computer Vision
Trust and health
Maintenance
- caffe
- Dormant (18%)
- lightly
- Very active (96%)
Days since push
- caffe
- 710d
- lightly
- 1d
Open issues (now)
- caffe
- 1.2k
- lightly
- 92
Full report
- caffe
- Trust report
- lightly
- Trust report
Choose caffe if…
- caffe is primarily C++; lightly is Python.
- License: caffe is Other, lightly is MIT.
- Tags unique to caffe: vision, c++.
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.
Choose lightly if…
- lightly is primarily Python; caffe is C++.
- License: lightly is MIT, caffe is Other.
- Tags unique to lightly: embeddings, hacktoberfest, pytorch, contributions-welcome.
- Also covers Model Training.
When NOT to use lightly
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (BVLC/caffe) · observed Jul 11, 2026
- GitHub forks (BVLC/caffe) · observed Jul 11, 2026
- Last push (BVLC/caffe) · observed Jul 31, 2024
- License file (Other) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (lightly-ai/lightly) · observed Jul 11, 2026
- GitHub forks (lightly-ai/lightly) · observed Jul 11, 2026
- Last push (lightly-ai/lightly) · observed Jul 9, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: caffe 35k · lightly 3.8k (synced Jul 11, 2026).
Common questions
- What is the difference between caffe and lightly?
- caffe: Caffe: a fast open framework for deep learning.. lightly: A python library for self-supervised learning on images.. See the comparison table for live GitHub stats and shared categories.
- When should I choose caffe over lightly?
- Choose caffe over lightly when caffe is primarily C++; lightly is Python; License: caffe is Other, lightly is MIT; Tags unique to caffe: vision, c++.
- When should I choose lightly over caffe?
- Choose lightly over caffe when lightly is primarily Python; caffe is C++; License: lightly is MIT, caffe is Other; Tags unique to lightly: embeddings, hacktoberfest, pytorch, contributions-welcome; 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 lightly?
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is caffe or lightly more popular on GitHub?
- caffe has more GitHub stars (34,574 vs 3,777). Stars measure visibility, not whether either tool fits your constraints.
- Are caffe and lightly open source?
- Yes - both are open-source projects on GitHub (caffe: Other, lightly: MIT).
- Where can I find alternatives to caffe or lightly?
- GraphCanon lists graph-backed alternatives at caffe alternatives and lightly alternatives (caffe markdown twin, lightly markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, caffe or lightly?
- caffe: Dormant. lightly: Very active. 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 lightly?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: caffe trust report; lightly trust report.