Comparison
pytorch-lightning vs openpi
Verdict
Pick pytorch-lightning if pyTorch Lightning scales PyTorch models across GPUs with minimal code changes; pick openpi if openpi is a repository for running AI models with specific GPU requirements for inference and fine-tuning, including LoRA and full fine-tuning modes.
Markdown twin · pytorch-lightning alternatives · openpi alternatives
GraphCanon updated Sep 27, 2026
11views this month
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Trust & integrity
| Signal | pytorch-lightning | openpi |
|---|---|---|
| Maintenance | Very active (5d since push) As of Sep 27, 2026 · github_public_v1 | Active (24d since push) As of Sep 18, 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 18, 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 Sep 18, 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.
- openpi
- Repository for running AI models with GPU requirements specified for inference and fine-tuning.
Stars
- pytorch-lightning
- 31k
- openpi
- 14k
Forks
- pytorch-lightning
- 3.8k
- openpi
- 2.5k
Open issues
- pytorch-lightning
- 1.1k
- openpi
- 345
Language
- pytorch-lightning
- Python
- openpi
- Python
Adopt for
- pytorch-lightning
- PyTorch Lightning scales PyTorch models across GPUs with minimal code changes.
- openpi
- openpi is a repository for running AI models with specific GPU requirements for inference and fine-tuning, including LoRA and full fine-tuning modes.
Persona
- pytorch-lightning
- -
- openpi
- -
Runtime
- pytorch-lightning
- -
- openpi
- -
License
- pytorch-lightning
- Apache-2.0
- openpi
- Apache-2.0
Last pushed
- pytorch-lightning
- Sep 21, 2026
- openpi
- Aug 24, 2026
Categories
- pytorch-lightning
- Inference & Serving, Model Training
- openpi
- Inference & Serving, Model Training
Trust and health
Maintenance
- pytorch-lightning
- Very active (96%)
- openpi
- Active (82%)
Days since push
- pytorch-lightning
- 5d
- openpi
- 24d
Open issues (now)
- pytorch-lightning
- 1.1k
- openpi
- 345
Stars delta
- pytorch-lightning
- +96 (30d)
- openpi
- +776 (30d)
Open issues delta
- pytorch-lightning
- +30 (30d)
- openpi
- +29 (30d)
OSV dependency advisories
- pytorch-lightning
- No published findings from this source as of 2026-07-11
- openpi
- No lockfile (source not queried)
Full report
- pytorch-lightning
- Trust report
- openpi
- Trust report
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 14k) - 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 openpi if…
- Requirements: The repository requires an NVIDIA GPU with at least 8 GB of memory for inference, 22.5 GB for fine-tuning with LoRA, and 70 GB for full fine-tuning..
- Tags unique to openpi: fine-tuning, gpu, inference, lora.
- Use openpi when you need to run AI models with precise GPU memory requirements for inference and fine-tuning, particularly with LoRA and full fine-tuning modes.
When NOT to use openpi
- Avoid using openpi if your project requires multi-node training, as the current training script does not support this feature.
- Do not use openpi if you are working on an operating system other than Ubuntu 22.04, as the repository has not been tested with other systems.
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 (Physical-Intelligence/openpi) · observed Sep 20, 2026
- GitHub forks (Physical-Intelligence/openpi) · observed Sep 20, 2026
- Last push (Physical-Intelligence/openpi) · observed Aug 24, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: pytorch-lightning 31k · openpi 14k (synced Sep 27, 2026).
Common questions
- What is the difference between pytorch-lightning and openpi?
- pytorch-lightning: Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.. openpi: Repository for running AI models with GPU requirements specified for inference and fine-tuning.. See the comparison table for live GitHub stats and shared categories.
- When should I choose pytorch-lightning over openpi?
- Choose pytorch-lightning over openpi 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 14k) - visibility, not fit.
- When should I choose openpi over pytorch-lightning?
- Choose openpi over pytorch-lightning when Requirements: The repository requires an NVIDIA GPU with at least 8 GB of memory for inference, 22.5 GB for fine-tuning with LoRA, and 70 GB for full fine-tuning.; Tags unique to openpi: fine-tuning, gpu, inference, lora; Use openpi when you need to run AI models with precise GPU memory requirements for inference and fine-tuning, particularly with LoRA and full fine-tuning modes.
- 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 openpi?
- Avoid using openpi if your project requires multi-node training, as the current training script does not support this feature. Do not use openpi if you are working on an operating system other than Ubuntu 22.04, as the repository has not been tested with other systems.
- Is pytorch-lightning or openpi more popular on GitHub?
- pytorch-lightning has more GitHub stars (31,363 vs 13,874). Stars measure visibility, not whether either tool fits your constraints.
- Are pytorch-lightning and openpi open source?
- Yes - both are open-source projects on GitHub (pytorch-lightning: Apache-2.0, openpi: Apache-2.0).
- Where can I find alternatives to pytorch-lightning or openpi?
- GraphCanon lists graph-backed alternatives at pytorch-lightning alternatives and openpi alternatives (pytorch-lightning markdown twin, openpi 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 openpi?
- pytorch-lightning: Very active. openpi: 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 pytorch-lightning and openpi?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: pytorch-lightning trust report; openpi trust report.