Home/Compare/lightly-train vs pytorch-lightning

Comparison

lightly-train vs pytorch-lightning

Verdict

Pick lightly-train when license: lightly-train is AGPL-3.0, pytorch-lightning is Apache-2.0; pick pytorch-lightning when license: pytorch-lightning is Apache-2.0, lightly-train is AGPL-3.0.

Markdown twin · lightly-train alternatives · pytorch-lightning alternatives

GraphCanon updated today

lightly-train logo

lightly-train

lightly-ai/lightly-train

1.6kpushed Jul 10, 2026
vs
pytorch-lightning logo

pytorch-lightning

Lightning-AI/pytorch-lightning

31kpushed Jul 10, 2026

Trust & integrity

Signallightly-trainpytorch-lightning
Maintenance
Very active (0d since push)
As of 1d · github_public_v1
Very active (1d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of 1d · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of 1d · none
No criticals
As of today · osv@v1

Tagline

lightly-train
All-in-one training for vision models: pretraining, fine-tuning, distillation.
pytorch-lightning
Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

Stars

lightly-train
1.6k
pytorch-lightning
31k

Forks

lightly-train
89
pytorch-lightning
3.8k

Open issues

lightly-train
64
pytorch-lightning
1.0k

Language

lightly-train
Python
pytorch-lightning
Python

Adopt for

lightly-train
Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation.
pytorch-lightning
-

Persona

lightly-train
-
pytorch-lightning
-

Runtime

lightly-train
-
pytorch-lightning
-

License

lightly-train
AGPL-3.0
pytorch-lightning
Apache-2.0

Last pushed

lightly-train
Jul 10, 2026
pytorch-lightning
Jul 10, 2026

Categories

lightly-train
Computer Vision, Model Training
pytorch-lightning
Computer Vision, Model Training

Trust and health

Days since push

lightly-train
0d
pytorch-lightning
1d

Open issues (now)

lightly-train
64
pytorch-lightning
1.0k

Security scan

lightly-train
No lockfile
pytorch-lightning
No criticals

Full report

lightly-train
Trust report
pytorch-lightning
Trust report

Choose lightly-train if…

  • License: lightly-train is AGPL-3.0, pytorch-lightning is Apache-2.0.
  • Requirements: Min 8 GB RAM.
  • Tags unique to lightly-train: computer-vision, contrastive-learning, depth-estimation, dinov2.
  • Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation.

When NOT to use lightly-train

  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

Choose pytorch-lightning if…

  • License: pytorch-lightning is Apache-2.0, lightly-train is AGPL-3.0.
  • Tags unique to pytorch-lightning: ai, artificial-intelligence, data-science, machine-learning.
  • More GitHub stars (31k vs 1.6k) - visibility, not fit.

When NOT to use pytorch-lightning

  • 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 on cards: lightly-train 1.6k · pytorch-lightning 31k (synced Jul 11, 2026).

Common questions

What is the difference between lightly-train and pytorch-lightning?
lightly-train: All-in-one training for vision models: pretraining, fine-tuning, distillation.. pytorch-lightning: Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.. See the comparison table for live GitHub stats and shared categories.
When should I choose lightly-train over pytorch-lightning?
Choose lightly-train over pytorch-lightning when License: lightly-train is AGPL-3.0, pytorch-lightning is Apache-2.0; Requirements: Min 8 GB RAM; Tags unique to lightly-train: computer-vision, contrastive-learning, depth-estimation, dinov2; Lightly-train is a Python-based framework focused on training vision models including YOLO, ViTs, RT-DETR, and DINOv3, offering comprehensive features like pretraining, fine-tuning, and distillation.
When should I choose pytorch-lightning over lightly-train?
Choose pytorch-lightning over lightly-train when License: pytorch-lightning is Apache-2.0, lightly-train is AGPL-3.0; Tags unique to pytorch-lightning: ai, artificial-intelligence, data-science, machine-learning; More GitHub stars (31k vs 1.6k) - visibility, not fit.
When should I avoid lightly-train?
Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
When should I avoid pytorch-lightning?
Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Is lightly-train or pytorch-lightning more popular on GitHub?
pytorch-lightning has more GitHub stars (31,233 vs 1,610). Stars measure visibility, not whether either tool fits your constraints.
Are lightly-train and pytorch-lightning open source?
Yes - both are open-source projects on GitHub (lightly-train: AGPL-3.0, pytorch-lightning: Apache-2.0).
Where can I find alternatives to lightly-train or pytorch-lightning?
GraphCanon lists graph-backed alternatives at lightly-train alternatives and pytorch-lightning alternatives (lightly-train markdown twin, pytorch-lightning 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, lightly-train or pytorch-lightning?
lightly-train: Very active. pytorch-lightning: 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 lightly-train and pytorch-lightning?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: lightly-train trust report; pytorch-lightning trust report.