--- title: "ormb vs openpi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kleveross-ormb-vs-physical-intelligence-openpi" tools: ["kleveross-ormb", "physical-intelligence-openpi"] --- # ormb vs openpi *GraphCanon updated Sep 30, 2026* ## Verdict Pick ormb if oRMB encapsulates machine learning and deep-learning models via OCI artifacts within Docker containers for streamlined model management; 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. [ormb](https://github.com/kleveross/ormb) reports 474 GitHub stars, 61 forks, and 32 open issues, last pushed Jan 26, 2024. [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 [ormb's repository](https://github.com/kleveross/ormb) and [openpi's repository](https://github.com/Physical-Intelligence/openpi). | | [ormb](/tools/kleveross-ormb.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Tagline | Docker for ML/DL Models Based on OCI Artifacts | Repository for running AI models with GPU requirements specified for inference and fine-tuning. | | Stars | 474 | 13,874 | | Forks | 61 | 2,467 | | Open issues | 32 | 345 | | Language | Go | Python | | Adopt for | ORMB encapsulates machine learning and deep-learning models via OCI artifacts within Docker containers for streamlined model management. | 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._ | | [ormb](/tools/kleveross-ormb.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Active (82%) | | Days since push | 978d | 24d | | Open issues (now) | 32 | 345 | | Stars delta | +1 (30d) | +776 (30d) | | Open issues delta | 0 (30d) | +29 (30d) | | Full report | [trust report](/tools/kleveross-ormb/trust.md) | [trust report](/tools/physical-intelligence-openpi/trust.md) | ## Decision facts: ormb - **Adopt for:** ORMB encapsulates machine learning and deep-learning models via OCI artifacts within Docker containers for streamlined model management. ## 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 ormb if… - ormb is primarily Go; openpi is Python. - Tags unique to ormb: docker, machine-learning, model-management, model-versioning. - If you need sophisticated version control for your ML/DL models through an image registry, ORMB provides this functionality. ### Choose openpi if… - openpi is primarily Python; ormb is Go. - 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 ormb - Should you seek simple models deployment without extensive version management features, ORMB may introduce unnecessary complexity. - If your project strictly avoids using Docker and OCI artifacts for model handling, then this tool would not be suitable. ## 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 ormb and openpi? ormb: Docker for ML/DL Models Based on OCI Artifacts. 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 ormb over openpi? Choose ormb over openpi when ormb is primarily Go; openpi is Python; Tags unique to ormb: docker, machine-learning, model-management, model-versioning; If you need sophisticated version control for your ML/DL models through an image registry, ORMB provides this functionality. ### When should I choose openpi over ormb? Choose openpi over ormb when openpi is primarily Python; ormb is Go; 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 ormb? Should you seek simple models deployment without extensive version management features, ORMB may introduce unnecessary complexity. If your project strictly avoids using Docker and OCI artifacts for model handling, then this tool would not be suitable. ### 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 ormb or openpi more popular on GitHub? openpi has more GitHub stars (13,874 vs 474). Stars measure visibility, not whether either tool fits your constraints. ### Are ormb and openpi open source? Yes - both are open-source projects on GitHub (ormb: Apache-2.0, openpi: Apache-2.0). ### Where can I find alternatives to ormb or openpi? GraphCanon lists graph-backed alternatives at [ormb alternatives](/tools/kleveross-ormb/alternatives) and [openpi alternatives](/tools/physical-intelligence-openpi/alternatives) ([ormb markdown twin](/tools/kleveross-ormb/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/kleveross-ormb-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, ormb or openpi? ormb: Dormant. 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 ormb and openpi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ormb trust report](/tools/kleveross-ormb/trust); [openpi trust report](/tools/physical-intelligence-openpi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kleveross-ormb`](/api/graphcanon/graph?tool=kleveross-ormb) - 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/_