--- title: "paper-qa vs google-research" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-house-paper-qa-vs-google-research-google-research" tools: ["future-house-paper-qa", "google-research-google-research"] --- # paper-qa vs google-research *GraphCanon updated Aug 18, 2026* ## Verdict Pick paper-qa if paperQA2 version 5 is a retrieval-augmented generation (RAG) system optimized for extracting information from scientific documents, enhancing user queries with citations; pick google-research if popular for its research-grade projects hosted by Google Research, this repository offers diverse machine-learning datasets and source files under specific licenses. [paper-qa](https://futurehouse.gitbook.io/futurehouse-cookbook) reports 9.0k GitHub stars, 907 forks, and 141 open issues, last pushed Aug 12, 2026. [google-research](https://research.google) has 38k stars, 8.5k forks, and 2.0k open issues, last pushed Jul 30, 2026. Figures are from public GitHub metadata via [paper-qa's repository](https://github.com/Future-House/paper-qa) and [google-research's repository](https://github.com/google-research/google-research). | | [paper-qa](/tools/future-house-paper-qa.md) | [google-research](/tools/google-research-google-research.md) | | --- | --- | --- | | Tagline | High accuracy RAG for answering questions from scientific documents with citations | Google Research Repository | | Stars | 9,048 | 38,480 | | Forks | 907 | 8,461 | | Open issues | 141 | 1,984 | | Language | Python | Jupyter Notebook | | Adopt for | PaperQA2 version 5 is a retrieval-augmented generation (RAG) system optimized for extracting information from scientific documents, enhancing user queries with citations. | Popular for its research-grade projects hosted by Google Research, this repository offers diverse machine-learning datasets and source files under specific licenses. | | Persona | - | - | | Runtime | - | - | | License | 'Apache-2.0' - Permissive free software license that allows for both non-commercial use and commercial exploitation of the package. | Code is under Apache-2.0 license while datasets are released under CC BY 4.0 International license. | | Categories | Data & Retrieval, Model Training | Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [paper-qa](/tools/future-house-paper-qa.md) | [google-research](/tools/google-research-google-research.md) | | --- | --- | --- | | Days since push | 5d | 6d | | Open issues (now) | 141 | 2.0k | | Stars delta | +154 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/future-house-paper-qa/trust.md) | [trust report](/tools/google-research-google-research/trust.md) | ## Decision facts: paper-qa - **Requirements:** Min 4 GB RAM - **Adopt for:** PaperQA2 version 5 is a retrieval-augmented generation (RAG) system optimized for extracting information from scientific documents, enhancing user queries with citations. - **License detail:** 'Apache-2.0' - Permissive free software license that allows for both non-commercial use and commercial exploitation of the package. ## Decision facts: google-research - **Requirements:** Requires a working understanding of how to navigate large repositories and selectively clone desired subdirectories. - **Adopt for:** Popular for its research-grade projects hosted by Google Research, this repository offers diverse machine-learning datasets and source files under specific licenses. - **License detail:** Code is under Apache-2.0 license while datasets are released under CC BY 4.0 International license. ## Choose when ### Choose paper-qa if… - paper-qa is primarily Python; google-research is Jupyter Notebook. - Requirements: Min 4 GB RAM. - Tags unique to paper-qa: rag, science, search. - Your project specifically requires processing and querying scientific documents, as PaperQA2 offers specialized capabilities tuned for this domain. ### Choose google-research if… - google-research is primarily Jupyter Notebook; paper-qa is Python. - Requirements: Requires a working understanding of how to navigate large repositories and selectively clone desired subdirectories.. - Tags unique to google-research: machine-learning, research. - When you need access to high-quality machine learning datasets released under the CC BY 4.0 International license alongside Apache-2.0 licensed code from Google researchers. ## When NOT to use paper-qa - If your use case does not involve scientific document processing, another RAG system better suited to your specific type of documents (e.g., legal, medical) might be more fitting. - In scenarios where real-time performance is critical and extensive indexing or access to external APIs for large-scale paper handling becomes a bottleneck. ## When NOT to use google-research - When the need is for simpler or more streamlined datasets that match different licensing needs apart from CC BY 4.0 International and Apache-2.0. - If you require a repository with an official product-level support guarantee from Google, as this resource has explicitly declared itself as non-official. ## Common questions ### What is the difference between paper-qa and google-research? paper-qa: High accuracy RAG for answering questions from scientific documents with citations. google-research: Google Research Repository. See the comparison table for live GitHub stats and shared categories. ### When should I choose paper-qa over google-research? Choose paper-qa over google-research when paper-qa is primarily Python; google-research is Jupyter Notebook; Requirements: Min 4 GB RAM; Tags unique to paper-qa: rag, science, search; Your project specifically requires processing and querying scientific documents, as PaperQA2 offers specialized capabilities tuned for this domain. ### When should I choose google-research over paper-qa? Choose google-research over paper-qa when google-research is primarily Jupyter Notebook; paper-qa is Python; Requirements: Requires a working understanding of how to navigate large repositories and selectively clone desired subdirectories.; Tags unique to google-research: machine-learning, research; When you need access to high-quality machine learning datasets released under the CC BY 4.0 International license alongside Apache-2.0 licensed code from Google researchers. ### When should I avoid paper-qa? If your use case does not involve scientific document processing, another RAG system better suited to your specific type of documents (e.g., legal, medical) might be more fitting. In scenarios where real-time performance is critical and extensive indexing or access to external APIs for large-scale paper handling becomes a bottleneck. ### When should I avoid google-research? When the need is for simpler or more streamlined datasets that match different licensing needs apart from CC BY 4.0 International and Apache-2.0. If you require a repository with an official product-level support guarantee from Google, as this resource has explicitly declared itself as non-official. ### Is paper-qa or google-research more popular on GitHub? google-research has more GitHub stars (38,480 vs 9,048). Stars measure visibility, not whether either tool fits your constraints. ### Are paper-qa and google-research open source? Yes - both are open-source projects on GitHub (paper-qa: Apache-2.0, google-research: Apache-2.0). ### Where can I find alternatives to paper-qa or google-research? GraphCanon lists graph-backed alternatives at [paper-qa alternatives](/tools/future-house-paper-qa/alternatives) and [google-research alternatives](/tools/google-research-google-research/alternatives) ([paper-qa markdown twin](/tools/future-house-paper-qa/alternatives.md), [google-research markdown twin](/tools/google-research-google-research/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/future-house-paper-qa-vs-google-research-google-research.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, paper-qa or google-research? paper-qa: Very active. google-research: Very 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 paper-qa and google-research? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [paper-qa trust report](/tools/future-house-paper-qa/trust); [google-research trust report](/tools/google-research-google-research/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=future-house-paper-qa`](/api/graphcanon/graph?tool=future-house-paper-qa) - 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/_