--- title: "local-deep-research vs open-webui" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/learningcircuit-local-deep-research-vs-open-webui-open-webui" tools: ["learningcircuit-local-deep-research", "open-webui-open-webui"] --- # local-deep-research vs open-webui *GraphCanon updated Jul 15, 2026* ## Verdict Pick local-deep-research when license: local-deep-research is MIT, open-webui is Other; pick open-webui when license: open-webui is Other, local-deep-research is MIT. [local-deep-research](https://github.com/LearningCircuit/local-deep-research) reports 8.7k GitHub stars, 767 forks, and 281 open issues, last pushed Jul 15, 2026. [open-webui](https://openwebui.com) has 145k stars, 21k forks, and 391 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [local-deep-research's repository](https://github.com/LearningCircuit/local-deep-research) and [open-webui's repository](https://github.com/open-webui/open-webui). | | [local-deep-research](/tools/learningcircuit-local-deep-research.md) | [open-webui](/tools/open-webui-open-webui.md) | | --- | --- | --- | | Tagline | ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encryp | User-friendly AI Interface (Supports Ollama, OpenAI API, ...) | | Stars | 8,719 | 145,029 | | Forks | 767 | 21,005 | | Open issues | 281 | 391 | | Language | Python | Python | | Adopt for | - | Suitable for developers working with large language models who require a user-friendly interface and support for multiple APIs including Ollama and OpenAI. | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | Data & Retrieval, Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [local-deep-research](/tools/learningcircuit-local-deep-research.md) | [open-webui](/tools/open-webui-open-webui.md) | | --- | --- | --- | | Open issues (now) | 281 | 391 | | Owner type | User | Organization | | Full report | [trust report](/tools/learningcircuit-local-deep-research/trust.md) | [trust report](/tools/open-webui-open-webui/trust.md) | ## Decision facts: open-webui - **Adopt for:** Suitable for developers working with large language models who require a user-friendly interface and support for multiple APIs including Ollama and OpenAI. ## Choose when ### Choose local-deep-research if… - License: local-deep-research is MIT, open-webui is Other. - Tags unique to local-deep-research: academia, anthropic, arxiv, brave. - Also covers Data & Retrieval. ### Choose open-webui if… - License: open-webui is Other, local-deep-research is MIT. - Tags unique to open-webui: ai, llm, openai, self-hosted. - When you need to integrate multiple AI services, such as Ollama and OpenAI, into a unified user interface. ## When NOT to use local-deep-research - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use open-webui - When looking for tooling that exclusively supports APIs other than Ollama and OpenAI, as these are specific areas of focus for open-webui. - If the requirement is a highly specialized interface tailored to specific tasks rather than a general AI interaction platform. ## Common questions ### What is the difference between local-deep-research and open-webui? local-deep-research: ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encryp. open-webui: User-friendly AI Interface (Supports Ollama, OpenAI API, ...). See the comparison table for live GitHub stats and shared categories. ### When should I choose local-deep-research over open-webui? Choose local-deep-research over open-webui when License: local-deep-research is MIT, open-webui is Other; Tags unique to local-deep-research: academia, anthropic, arxiv, brave; Also covers Data & Retrieval. ### When should I choose open-webui over local-deep-research? Choose open-webui over local-deep-research when License: open-webui is Other, local-deep-research is MIT; Tags unique to open-webui: ai, llm, openai, self-hosted; When you need to integrate multiple AI services, such as Ollama and OpenAI, into a unified user interface. ### When should I avoid local-deep-research? Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid open-webui? When looking for tooling that exclusively supports APIs other than Ollama and OpenAI, as these are specific areas of focus for open-webui. If the requirement is a highly specialized interface tailored to specific tasks rather than a general AI interaction platform. ### Is local-deep-research or open-webui more popular on GitHub? open-webui has more GitHub stars (145,029 vs 8,719). Stars measure visibility, not whether either tool fits your constraints. ### Are local-deep-research and open-webui open source? Yes - both are open-source projects on GitHub (local-deep-research: MIT, open-webui: Other). ### Where can I find alternatives to local-deep-research or open-webui? GraphCanon lists graph-backed alternatives at [local-deep-research alternatives](/tools/learningcircuit-local-deep-research/alternatives) and [open-webui alternatives](/tools/open-webui-open-webui/alternatives) ([local-deep-research markdown twin](/tools/learningcircuit-local-deep-research/alternatives.md), [open-webui markdown twin](/tools/open-webui-open-webui/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/learningcircuit-local-deep-research-vs-open-webui-open-webui.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, local-deep-research or open-webui? local-deep-research: Very active. open-webui: 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 local-deep-research and open-webui? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [local-deep-research trust report](/tools/learningcircuit-local-deep-research/trust); [open-webui trust report](/tools/open-webui-open-webui/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=learningcircuit-local-deep-research`](/api/graphcanon/graph?tool=learningcircuit-local-deep-research) - 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/_