--- title: "open-webui vs deep-research" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/open-webui-open-webui-vs-u14app-deep-research" tools: ["open-webui-open-webui", "u14app-deep-research"] --- # open-webui vs deep-research *GraphCanon updated Jul 15, 2026* ## Verdict Pick open-webui when open-webui is primarily Python; deep-research is JavaScript; pick deep-research when deep-research is primarily JavaScript; open-webui is Python. [open-webui](https://openwebui.com) reports 145k GitHub stars, 21k forks, and 391 open issues, last pushed Jul 10, 2026. [deep-research](https://research.u14.app) has 4.6k stars, 1.1k forks, and 36 open issues, last pushed Jun 18, 2026. Figures are from public GitHub metadata via [open-webui's repository](https://github.com/open-webui/open-webui) and [deep-research's repository](https://github.com/u14app/deep-research). | | [open-webui](/tools/open-webui-open-webui.md) | [deep-research](/tools/u14app-deep-research.md) | | --- | --- | --- | | Tagline | User-friendly AI Interface (Supports Ollama, OpenAI API, ...) | Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server. | | Stars | 145,029 | 4,632 | | Forks | 21,005 | 1,055 | | Open issues | 391 | 36 | | Language | Python | JavaScript | | 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 | Other | MIT | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [open-webui](/tools/open-webui-open-webui.md) | [deep-research](/tools/u14app-deep-research.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 26d | | Open issues (now) | 391 | 36 | | Full report | [trust report](/tools/open-webui-open-webui/trust.md) | [trust report](/tools/u14app-deep-research/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 open-webui if… - open-webui is primarily Python; deep-research is JavaScript. - License: open-webui is Other, 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. ### Choose deep-research if… - deep-research is primarily JavaScript; open-webui is Python. - License: deep-research is MIT, open-webui is Other. - Tags unique to deep-research: anthropic, deep-research, deep-research-api, deepresearch. - Also covers Vector Databases. - deep-research ships Docker support for self-hosted deployment. ## 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. ## When NOT to use deep-research - 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. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between open-webui and deep-research? open-webui: User-friendly AI Interface (Supports Ollama, OpenAI API, ...). deep-research: Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.. See the comparison table for live GitHub stats and shared categories. ### When should I choose open-webui over deep-research? Choose open-webui over deep-research when open-webui is primarily Python; deep-research is JavaScript; License: open-webui is Other, 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 choose deep-research over open-webui? Choose deep-research over open-webui when deep-research is primarily JavaScript; open-webui is Python; License: deep-research is MIT, open-webui is Other; Tags unique to deep-research: anthropic, deep-research, deep-research-api, deepresearch; Also covers Vector Databases; deep-research ships Docker support for self-hosted deployment. ### 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. ### When should I avoid deep-research? 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. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is open-webui or deep-research more popular on GitHub? open-webui has more GitHub stars (145,029 vs 4,632). Stars measure visibility, not whether either tool fits your constraints. ### Are open-webui and deep-research open source? Yes - both are open-source projects on GitHub (open-webui: Other, deep-research: MIT). ### Where can I find alternatives to open-webui or deep-research? GraphCanon lists graph-backed alternatives at [open-webui alternatives](/tools/open-webui-open-webui/alternatives) and [deep-research alternatives](/tools/u14app-deep-research/alternatives) ([open-webui markdown twin](/tools/open-webui-open-webui/alternatives.md), [deep-research markdown twin](/tools/u14app-deep-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/open-webui-open-webui-vs-u14app-deep-research.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, open-webui or deep-research? open-webui: Very active. deep-research: 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 open-webui and deep-research? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [open-webui trust report](/tools/open-webui-open-webui/trust); [deep-research trust report](/tools/u14app-deep-research/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=open-webui-open-webui`](/api/graphcanon/graph?tool=open-webui-open-webui) - 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/_