--- title: "openpi vs chipper" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/physical-intelligence-openpi-vs-tilmangriesel-chipper" tools: ["physical-intelligence-openpi", "tilmangriesel-chipper"] --- # openpi vs chipper *GraphCanon updated Aug 25, 2026* ## Verdict Pick openpi if openpi is a specialized tool for model training, inference & serving that leverages advanced GPU capabilities and has specific requirements for memory and hardware configurations; pick chipper if chipper is an AI interface tool for tinkerers that supports agentic-AI functionalities and LLM inference using Hugging Face models, including Phi4, with Haystack RAG for retrieval-augmented generation. [openpi](https://github.com/Physical-Intelligence/openpi) reports 13k GitHub stars, 2.3k forks, and 316 open issues, last pushed Jun 16, 2026. [chipper](https://chipper.tilmangriesel.com/) has 483 stars, 47 forks, and 6 open issues, last pushed May 19, 2026. Figures are from public GitHub metadata via [openpi's repository](https://github.com/Physical-Intelligence/openpi) and [chipper's repository](https://github.com/TilmanGriesel/chipper). | | [openpi](/tools/physical-intelligence-openpi.md) | [chipper](/tools/tilmangriesel-chipper.md) | | --- | --- | --- | | Tagline | Repository for running AI models with GPU requirements specified. | AI interface for tinkerers using Ollama and Haystack RAG | | Stars | 13,098 | 483 | | Forks | 2,276 | 47 | | Open issues | 316 | 6 | | Language | Python | Python | | 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. | Chipper is an AI interface tool for tinkerers that supports agentic-AI functionalities and LLM inference using Hugging Face models, including Phi4, with Haystack RAG for retrieval-augmented generation. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Inference & Serving, Model Training | AI Agents, Evaluation & Observability, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openpi](/tools/physical-intelligence-openpi.md) | [chipper](/tools/tilmangriesel-chipper.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 46d | 97d | | Open issues (now) | 316 | 6 | | Stars delta | Unknown | -1 (30d) | | Open issues delta | Unknown | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/physical-intelligence-openpi/trust.md) | [trust report](/tools/tilmangriesel-chipper/trust.md) | ## 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. ## Decision facts: chipper - **Adopt for:** Chipper is an AI interface tool for tinkerers that supports agentic-AI functionalities and LLM inference using Hugging Face models, including Phi4, with Haystack RAG for retrieval-augmented generation. - **License detail:** MIT - **Runtime:** unknown ## Choose when ### Choose openpi if… - License: openpi is Apache-2.0, chipper is MIT. - 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. ### Choose chipper if… - License: chipper is MIT, openpi is Apache-2.0. - Tags unique to chipper: agent, deepseek-chat, embedding, llm-inference. - Also covers AI Agents, Evaluation & Observability. - When you require an environment that integrates with Ollama API. ## 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. ## When NOT to use chipper - When the development requires real-time processing that is not aligned with Ollama's APIs or RAG capabilities. - If your project strictly adheres to proprietary AI interfaces, and external integrations like Haystack RAG are prohibited. - For teams preferring frameworks or tools that do not support agentic-AI features found in Chipper. ## Common questions ### What is the difference between openpi and chipper? openpi: Repository for running AI models with GPU requirements specified.. chipper: AI interface for tinkerers using Ollama and Haystack RAG. See the comparison table for live GitHub stats and shared categories. ### When should I choose openpi over chipper? Choose openpi over chipper when License: openpi is Apache-2.0, chipper is MIT; 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 choose chipper over openpi? Choose chipper over openpi when License: chipper is MIT, openpi is Apache-2.0; Tags unique to chipper: agent, deepseek-chat, embedding, llm-inference; Also covers AI Agents, Evaluation & Observability; When you require an environment that integrates with Ollama API. ### 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. ### When should I avoid chipper? When the development requires real-time processing that is not aligned with Ollama's APIs or RAG capabilities. If your project strictly adheres to proprietary AI interfaces, and external integrations like Haystack RAG are prohibited. For teams preferring frameworks or tools that do not support agentic-AI features found in Chipper. ### Is openpi or chipper more popular on GitHub? openpi has more GitHub stars (13,098 vs 483). Stars measure visibility, not whether either tool fits your constraints. ### Are openpi and chipper open source? Yes - both are open-source projects on GitHub (openpi: Apache-2.0, chipper: MIT). ### Where can I find alternatives to openpi or chipper? GraphCanon lists graph-backed alternatives at [openpi alternatives](/tools/physical-intelligence-openpi/alternatives) and [chipper alternatives](/tools/tilmangriesel-chipper/alternatives) ([openpi markdown twin](/tools/physical-intelligence-openpi/alternatives.md), [chipper markdown twin](/tools/tilmangriesel-chipper/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/physical-intelligence-openpi-vs-tilmangriesel-chipper.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openpi or chipper? openpi: Steady. chipper: Slowing. 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 openpi and chipper? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [openpi trust report](/tools/physical-intelligence-openpi/trust); [chipper trust report](/tools/tilmangriesel-chipper/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=physical-intelligence-openpi`](/api/graphcanon/graph?tool=physical-intelligence-openpi) - 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/_