Comparison
stable-diffusion vs lightly
Verdict
Pick stable-diffusion when stable-diffusion is primarily Jupyter Notebook; lightly is Python; pick lightly when lightly is primarily Python; stable-diffusion is Jupyter Notebook.
Markdown twin · stable-diffusion alternatives · lightly alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | stable-diffusion | lightly |
|---|---|---|
| Maintenance | Dormant (753d 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
- stable-diffusion
- A latent text-to-image diffusion model
- lightly
- A python library for self-supervised learning on images.
Stars
- stable-diffusion
- 73k
- lightly
- 3.8k
Forks
- stable-diffusion
- 11k
- lightly
- 339
Open issues
- stable-diffusion
- 617
- lightly
- 92
Language
- stable-diffusion
- Jupyter Notebook
- lightly
- Python
Adopt for
- stable-diffusion
- -
- lightly
- -
Persona
- stable-diffusion
- -
- lightly
- -
Runtime
- stable-diffusion
- -
- lightly
- -
License
- stable-diffusion
- Other
- lightly
- MIT
Last pushed
- stable-diffusion
- Jun 18, 2024
- lightly
- Jul 9, 2026
Categories
- stable-diffusion
- Model Training, Computer Vision
- lightly
- Vector Databases, Model Training, Computer Vision
Trust and health
Maintenance
- stable-diffusion
- Dormant (18%)
- lightly
- Very active (96%)
Days since push
- stable-diffusion
- 753d
- lightly
- 1d
Open issues (now)
- stable-diffusion
- 617
- lightly
- 92
Full report
- stable-diffusion
- Trust report
- lightly
- Trust report
Choose stable-diffusion if…
- stable-diffusion is primarily Jupyter Notebook; lightly is Python.
- License: stable-diffusion is Other, lightly is MIT.
- Tags unique to stable-diffusion: jupyter notebook.
When NOT to use stable-diffusion
- Last GitHub push was 754 days ago (dormant maintenance, Jun 18, 2024). Validate activity before betting a new project on stable-diffusion.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Choose lightly if…
- lightly is primarily Python; stable-diffusion is Jupyter Notebook.
- License: lightly is MIT, stable-diffusion is Other.
- Tags unique to lightly: embeddings, deep-learning, machine-learning, hacktoberfest.
- Also covers Vector Databases.
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 (CompVis/stable-diffusion) · observed Jul 11, 2026
- GitHub forks (CompVis/stable-diffusion) · observed Jul 11, 2026
- Last push (CompVis/stable-diffusion) · observed Jun 18, 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: stable-diffusion 73k · lightly 3.8k (synced Jul 11, 2026).
Common questions
- What is the difference between stable-diffusion and lightly?
- stable-diffusion: A latent text-to-image diffusion model. 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 stable-diffusion over lightly?
- Choose stable-diffusion over lightly when stable-diffusion is primarily Jupyter Notebook; lightly is Python; License: stable-diffusion is Other, lightly is MIT; Tags unique to stable-diffusion: jupyter notebook.
- When should I choose lightly over stable-diffusion?
- Choose lightly over stable-diffusion when lightly is primarily Python; stable-diffusion is Jupyter Notebook; License: lightly is MIT, stable-diffusion is Other; Tags unique to lightly: embeddings, deep-learning, machine-learning, hacktoberfest; Also covers Vector Databases.
- When should I avoid stable-diffusion?
- Last GitHub push was 754 days ago (dormant maintenance, Jun 18, 2024). Validate activity before betting a new project on stable-diffusion. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- 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 stable-diffusion or lightly more popular on GitHub?
- stable-diffusion has more GitHub stars (73,179 vs 3,777). Stars measure visibility, not whether either tool fits your constraints.
- Are stable-diffusion and lightly open source?
- Yes - both are open-source projects on GitHub (stable-diffusion: Other, lightly: MIT).
- Where can I find alternatives to stable-diffusion or lightly?
- GraphCanon lists graph-backed alternatives at stable-diffusion alternatives and lightly alternatives (stable-diffusion 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, stable-diffusion or lightly?
- stable-diffusion: 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 stable-diffusion and lightly?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: stable-diffusion trust report; lightly trust report.