--- title: "agenta vs openpi" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agenta-ai-agenta-vs-physical-intelligence-openpi" tools: ["agenta-ai-agenta", "physical-intelligence-openpi"] --- # agenta vs openpi *GraphCanon updated Jul 12, 2026* ## Verdict Pick agenta if agenta is an open-source LLMOps platform that supports prompt engineering, evaluation of language models, and monitoring their performance. It can be self-hosted and comes with a comprehensive set of tools for managing L; pick openpi if openpi is a specialized tool for model training, inference & serving that leverages advanced GPU capabilities and has specific requirements for. [agenta](http://www.agenta.ai) reports 4.3k GitHub stars, 565 forks, and 184 open issues, last pushed Jul 11, 2026. [openpi](https://github.com/Physical-Intelligence/openpi) has 13k stars, 2.2k forks, and 312 open issues, last pushed Jun 16, 2026. Figures are from public GitHub metadata via [agenta's repository](https://github.com/Agenta-AI/agenta) and [openpi's repository](https://github.com/Physical-Intelligence/openpi). | | [agenta](/tools/agenta-ai-agenta.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Tagline | The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place. | Repository for running AI models with GPU requirements specified. | | Stars | 4,283 | 12,742 | | Forks | 565 | 2,187 | | Open issues | 184 | 312 | | Language | TypeScript | Python | | Adopt for | Agenta is an open-source LLMOps platform that supports prompt engineering, evaluation of language models, and monitoring their performance. It can be self-hosted and comes with a comprehensive set of tools for managing L | openpi is a specialized tool for model training, inference & serving that leverages advanced GPU capabilities and has specific requirements for memory and hardware configurations. | | Persona | - | - | | Runtime | - | - | | License | Other | Apache-2.0 | | Categories | AI Agents, Inference & Serving, LLM Frameworks | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agenta](/tools/agenta-ai-agenta.md) | [openpi](/tools/physical-intelligence-openpi.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 25d | | Open issues (now) | 184 | 312 | | Full report | [trust report](/tools/agenta-ai-agenta/trust.md) | [trust report](/tools/physical-intelligence-openpi/trust.md) | ## Decision facts: agenta - **Adopt for:** Agenta is an open-source LLMOps platform that supports prompt engineering, evaluation of language models, and monitoring their performance. It can be self-hosted and comes with a comprehensive set of tools for managing L ## Decision facts: openpi - **Adopt for:** openpi is a specialized tool for model training, inference & serving that leverages advanced GPU capabilities and has specific requirements for memory and hardware configurations. ## Choose when ### Choose agenta if… - agenta is primarily TypeScript; openpi is Python. - License: agenta is Other, openpi is Apache-2.0. - Tags unique to agenta: agents, evaluation, llm-as-a-judge, llm-evaluation. - Also covers AI Agents, LLM Frameworks. - You should use Agenta if you're working on managing prompts and evaluating the performance of your language models while needing observability features in an open-source environment. ### Choose openpi if… - openpi is primarily Python; agenta is TypeScript. - License: openpi is Apache-2.0, agenta is Other. - Tags unique to openpi: fine-tuning, lora, model parallelism, nvidia gpu. - Also covers Model Training. - When you have an NVIDIA GPU with at least 8 GB of VRAM for inference or at least 22.5 GB to fine-tune models using LoRA (Low-Rank Adaptation) on a single GPU. ## When NOT to use agenta - Avoid Agenta if you prefer pre-packaged SaaS solutions over DIY open-source deployments; setting up and maintaining can be complex. - Agenta may not be suitable if your project or organization does not have the technical know-how to handle self-hosted environments, as configuration and deployment require specific Docker setup. ## When NOT to use openpi - When your project is not compatible with Ubuntu 22.04 or if you do not have access to a supported GPU configuration. - If you need to support multi-node training, as this capability has yet to be implemented in the current version of openpi. ## Common questions ### What is the difference between agenta and openpi? agenta: The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.. openpi: Repository for running AI models with GPU requirements specified.. See the comparison table for live GitHub stats and shared categories. ### When should I choose agenta over openpi? Choose agenta over openpi when agenta is primarily TypeScript; openpi is Python; License: agenta is Other, openpi is Apache-2.0; Tags unique to agenta: agents, evaluation, llm-as-a-judge, llm-evaluation; Also covers AI Agents, LLM Frameworks; You should use Agenta if you're working on managing prompts and evaluating the performance of your language models while needing observability features in an open-source environment. ### When should I choose openpi over agenta? Choose openpi over agenta when openpi is primarily Python; agenta is TypeScript; License: openpi is Apache-2.0, agenta is Other; Tags unique to openpi: fine-tuning, lora, model parallelism, nvidia gpu; Also covers Model Training; When you have an NVIDIA GPU with at least 8 GB of VRAM for inference or at least 22.5 GB to fine-tune models using LoRA (Low-Rank Adaptation) on a single GPU. ### When should I avoid agenta? Avoid Agenta if you prefer pre-packaged SaaS solutions over DIY open-source deployments; setting up and maintaining can be complex. Agenta may not be suitable if your project or organization does not have the technical know-how to handle self-hosted environments, as configuration and deployment require specific Docker setup. ### When should I avoid openpi? When your project is not compatible with Ubuntu 22.04 or if you do not have access to a supported GPU configuration. If you need to support multi-node training, as this capability has yet to be implemented in the current version of openpi. ### Is agenta or openpi more popular on GitHub? openpi has more GitHub stars (12,742 vs 4,283). Stars measure visibility, not whether either tool fits your constraints. ### Are agenta and openpi open source? Yes - both are open-source projects on GitHub (agenta: Other, openpi: Apache-2.0). ### Where can I find alternatives to agenta or openpi? GraphCanon lists graph-backed alternatives at [agenta alternatives](/tools/agenta-ai-agenta/alternatives) and [openpi alternatives](/tools/physical-intelligence-openpi/alternatives) ([agenta markdown twin](/tools/agenta-ai-agenta/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/agenta-ai-agenta-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, agenta or openpi? agenta: 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 agenta and openpi? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agenta trust report](/tools/agenta-ai-agenta/trust); [openpi trust report](/tools/physical-intelligence-openpi/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agenta-ai-agenta`](/api/graphcanon/graph?tool=agenta-ai-agenta) - 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/_