--- title: "pytorch-lightning vs openpi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lightning-ai-pytorch-lightning-vs-physical-intelligence-openpi" tools: ["lightning-ai-pytorch-lightning", "physical-intelligence-openpi"] --- # pytorch-lightning vs openpi *GraphCanon updated Sep 27, 2026* ## 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. [pytorch-lightning](https://lightning.ai/pytorch-lightning/?utm_source=ptl_readme&utm_medium=referral&utm_campaign=ptl_readme) reports 31k GitHub stars, 3.8k forks, and 1.1k open issues, last pushed Sep 21, 2026. [openpi](https://github.com/Physical-Intelligence/openpi) has 14k stars, 2.5k forks, and 345 open issues, last pushed Aug 24, 2026. Figures are from public GitHub metadata via [pytorch-lightning's repository](https://github.com/Lightning-AI/pytorch-lightning) and [openpi's repository](https://github.com/Physical-Intelligence/openpi). | | [pytorch-lightning](/tools/lightning-ai-pytorch-lightning.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Tagline | Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes. | Repository for running AI models with GPU requirements specified for inference and fine-tuning. | | Stars | 31,363 | 13,874 | | Forks | 3,801 | 2,467 | | Open issues | 1,090 | 345 | | Language | Python | Python | | Adopt for | PyTorch Lightning scales PyTorch models across GPUs with minimal code changes. | 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 | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Inference & Serving, Model Training | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [pytorch-lightning](/tools/lightning-ai-pytorch-lightning.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 5d | 24d | | Open issues (now) | 1.1k | 345 | | Stars delta | +96 (30d) | +776 (30d) | | Open issues delta | +30 (30d) | +29 (30d) | | Full report | [trust report](/tools/lightning-ai-pytorch-lightning/trust.md) | [trust report](/tools/physical-intelligence-openpi/trust.md) | ## Decision facts: pytorch-lightning - **Adopt for:** PyTorch Lightning scales PyTorch models across GPUs with minimal code changes. ## Decision facts: openpi - **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. - **Adopt for:** openpi is a repository for running AI models with specific GPU requirements for inference and fine-tuning, including LoRA and full fine-tuning modes. ## Choose when ### 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. ### 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 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 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. ## 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](/tools/lightning-ai-pytorch-lightning/alternatives) and [openpi alternatives](/tools/physical-intelligence-openpi/alternatives) ([pytorch-lightning markdown twin](/tools/lightning-ai-pytorch-lightning/alternatives.md), [openpi markdown twin](/tools/physical-intelligence-openpi/alternatives.md)), 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](/compare/lightning-ai-pytorch-lightning-vs-physical-intelligence-openpi.md) 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](/tools/lightning-ai-pytorch-lightning/trust); [openpi trust report](/tools/physical-intelligence-openpi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lightning-ai-pytorch-lightning`](/api/graphcanon/graph?tool=lightning-ai-pytorch-lightning) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_