Comparison
pytorch-lightning vs octoml-profile
Verdict
Pick pytorch-lightning if pyTorch Lightning scales PyTorch models across GPUs with minimal code changes; pick octoml-profile if octoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities.
Markdown twin · pytorch-lightning alternatives · octoml-profile alternatives
GraphCanon updated Sep 30, 2026
10views this month
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Trust & integrity
| Signal | pytorch-lightning | octoml-profile |
|---|---|---|
| Maintenance | Very active (5d since push) As of Sep 27, 2026 · github_public_v1 | Dormant (1254d since push) As of Sep 30, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 27, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 30, 2026 · github_public_v1 |
| OSV dependency advisories | No published findings from this source as of 2026-07-11 As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- pytorch-lightning
- Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.
- octoml-profile
- Home for OctoML PyTorch Profiler
Stars
- pytorch-lightning
- 31k
- octoml-profile
- 113
Forks
- pytorch-lightning
- 3.8k
- octoml-profile
- 10
Open issues
- pytorch-lightning
- 1.1k
- octoml-profile
- 0
Language
- pytorch-lightning
- Python
- octoml-profile
- -
Adopt for
- pytorch-lightning
- PyTorch Lightning scales PyTorch models across GPUs with minimal code changes.
- octoml-profile
- OctoML PyTorch Profiler provides profiling and acceleration tools for PyTorch models with remote execution capabilities.
Persona
- pytorch-lightning
- -
- octoml-profile
- -
Runtime
- pytorch-lightning
- -
- octoml-profile
- -
License
- pytorch-lightning
- Apache-2.0
- octoml-profile
- Apache-2.0
Last pushed
- pytorch-lightning
- Sep 21, 2026
- octoml-profile
- Apr 24, 2023
Categories
- pytorch-lightning
- Inference & Serving, Model Training
- octoml-profile
- Inference & Serving, Model Training
Trust and health
Maintenance
- pytorch-lightning
- Very active (96%)
- octoml-profile
- Dormant (18%)
Days since push
- pytorch-lightning
- 5d
- octoml-profile
- 1254d
Open issues (now)
- pytorch-lightning
- 1.1k
- octoml-profile
- 0
Stars delta
- pytorch-lightning
- +96 (30d)
- octoml-profile
- 0 (30d)
Open issues delta
- pytorch-lightning
- +30 (30d)
- octoml-profile
- 0 (30d)
OSV dependency advisories
- pytorch-lightning
- No published findings from this source as of 2026-07-11
- octoml-profile
- No lockfile (source not queried)
Full report
- pytorch-lightning
- Trust report
- octoml-profile
- Trust report
Shared compatibility
- Python · pytorch-lightning: Python runtime · octoml-profile: Python runtime
Choose pytorch-lightning if…
- Tags unique to pytorch-lightning: ai, artificial-intelligence, data-science, deep-learning.
- Scalable ML model training with consistent API across single to multiple GPUs
- More GitHub stars (31k vs 113) - visibility, not fit.
When NOT to use pytorch-lightning
- For lightweight models requiring minimal configuration or manual control over model distribution
- Projects that target environments without access to multi-GPU setups and do not require scalability features
Choose octoml-profile if…
- Tags unique to octoml-profile: acceleration, performance optimization, profiling.
- Need precise performance metrics on different backend architectures like CPU, GPU in cloud environments
- Leaner open-issue backlog (0).
When NOT to use octoml-profile
- Development for local, offline usage only without remote profiling needs
- Working with PyTorch versions below 2.0 or incompatible with specific CUDA/Apple silicon versions outlined in installation guide
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Lightning-AI/pytorch-lightning) · observed Sep 27, 2026
- GitHub forks (Lightning-AI/pytorch-lightning) · observed Sep 27, 2026
- Last push (Lightning-AI/pytorch-lightning) · observed Sep 21, 2026
- License file (Apache-2.0) · observed Sep 27, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (octoml/octoml-profile) · observed Sep 30, 2026
- GitHub forks (octoml/octoml-profile) · observed Sep 30, 2026
- Last push (octoml/octoml-profile) · observed Apr 24, 2023
- License file (Apache-2.0) · observed Sep 30, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: pytorch-lightning 31k · octoml-profile 113 (synced Sep 27, 2026).
Common questions
- What is the difference between pytorch-lightning and octoml-profile?
- pytorch-lightning: Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.. octoml-profile: Home for OctoML PyTorch Profiler. See the comparison table for live GitHub stats and shared categories.
- When should I choose pytorch-lightning over octoml-profile?
- Choose pytorch-lightning over octoml-profile when Tags unique to pytorch-lightning: ai, artificial-intelligence, data-science, deep-learning; Scalable ML model training with consistent API across single to multiple GPUs; More GitHub stars (31k vs 113) - visibility, not fit.
- When should I choose octoml-profile over pytorch-lightning?
- Choose octoml-profile over pytorch-lightning when Tags unique to octoml-profile: acceleration, performance optimization, profiling; Need precise performance metrics on different backend architectures like CPU, GPU in cloud environments; Leaner open-issue backlog (0).
- When should I avoid pytorch-lightning?
- For lightweight models requiring minimal configuration or manual control over model distribution Projects that target environments without access to multi-GPU setups and do not require scalability features
- When should I avoid octoml-profile?
- Development for local, offline usage only without remote profiling needs Working with PyTorch versions below 2.0 or incompatible with specific CUDA/Apple silicon versions outlined in installation guide
- Is pytorch-lightning or octoml-profile more popular on GitHub?
- pytorch-lightning has more GitHub stars (31,363 vs 113). Stars measure visibility, not whether either tool fits your constraints.
- Are pytorch-lightning and octoml-profile open source?
- Yes - both are open-source projects on GitHub (pytorch-lightning: Apache-2.0, octoml-profile: Apache-2.0).
- Where can I find alternatives to pytorch-lightning or octoml-profile?
- GraphCanon lists graph-backed alternatives at pytorch-lightning alternatives and octoml-profile alternatives (pytorch-lightning markdown twin, octoml-profile 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, pytorch-lightning or octoml-profile?
- pytorch-lightning: Very active. octoml-profile: Dormant. 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 pytorch-lightning and octoml-profile?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: pytorch-lightning trust report; octoml-profile trust report.