--- title: "litgpt vs openpi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lightning-ai-litgpt-vs-physical-intelligence-openpi" tools: ["lightning-ai-litgpt", "physical-intelligence-openpi"] --- # litgpt vs openpi *GraphCanon updated Sep 20, 2026* ## Verdict Pick litgpt if litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license; 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. [litgpt](https://lightning.ai) reports 14k GitHub stars, 1.5k forks, and 290 open issues, last pushed Sep 14, 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 [litgpt's repository](https://github.com/Lightning-AI/litgpt) and [openpi's repository](https://github.com/Physical-Intelligence/openpi). | | [litgpt](/tools/lightning-ai-litgpt.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Tagline | High-performance LLMs for pretraining, finetuning, and deployment | Repository for running AI models with GPU requirements specified for inference and fine-tuning. | | Stars | 13,667 | 13,874 | | Forks | 1,503 | 2,467 | | Open issues | 290 | 345 | | Language | Python | Python | | Adopt for | litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license. | 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, LLM Frameworks, Model Training | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [litgpt](/tools/lightning-ai-litgpt.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 3d | 24d | | Open issues (now) | 290 | 345 | | Stars delta | +62 (30d) | +776 (30d) | | Open issues delta | +18 (30d) | +29 (30d) | | Full report | [trust report](/tools/lightning-ai-litgpt/trust.md) | [trust report](/tools/physical-intelligence-openpi/trust.md) | ## Decision facts: litgpt - **Adopt for:** litgpt offers a suite of over 20 high-performance large language models, with tools for pretraining, finetuning, and deployment at scale, all under the Apache-2.0 license. ## 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 litgpt if… - Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models. - Also covers LLM Frameworks. - When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment. ### 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 litgpt - If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based. - When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases. - If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license. ## 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 litgpt and openpi? litgpt: High-performance LLMs for pretraining, finetuning, and deployment. 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 litgpt over openpi? Choose litgpt over openpi when Tags unique to litgpt: ai, artificial-intelligence, deep-learning, large-language-models; Also covers LLM Frameworks; When you need a comprehensive set of over 20 high-performance LLMs for pretraining, finetuning, and deployment. ### When should I choose openpi over litgpt? Choose openpi over litgpt 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 litgpt? If you are looking for a tool that supports languages other than Python, as litgpt is exclusively Python-based. When you need a tool that offers fewer model options, as litgpt provides over 20 models which might be overwhelming for specific use cases. If you require proprietary licensing, as litgpt is open-source under the Apache-2.0 license. ### 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 litgpt or openpi more popular on GitHub? openpi has more GitHub stars (13,874 vs 13,667). Stars measure visibility, not whether either tool fits your constraints. ### Are litgpt and openpi open source? Yes - both are open-source projects on GitHub (litgpt: Apache-2.0, openpi: Apache-2.0). ### Where can I find alternatives to litgpt or openpi? GraphCanon lists graph-backed alternatives at [litgpt alternatives](/tools/lightning-ai-litgpt/alternatives) and [openpi alternatives](/tools/physical-intelligence-openpi/alternatives) ([litgpt markdown twin](/tools/lightning-ai-litgpt/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-litgpt-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, litgpt or openpi? litgpt: 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 litgpt and openpi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [litgpt trust report](/tools/lightning-ai-litgpt/trust); [openpi trust report](/tools/physical-intelligence-openpi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lightning-ai-litgpt`](/api/graphcanon/graph?tool=lightning-ai-litgpt) - 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/_