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.
Running a deep-research assistant on your own hardware with citations, across local or cloud models and a choice of search engines.
You cannot provide local GPU capacity or configure search-engine access; the results the project reports are measured on a single local GPU with multiple engines configured.
About local-deep-research
Performs deep, agentic research using multiple LLMs and search engines with proper citations
First open-source project — fully-local on a single RTX 3090 (Qwen3.6-27B) — to report ~95% SimpleQA (n=500) and 77% xbench-DeepSearch (n=100) on local hardware. See the r/LocalLLaMA announcement and the benchmark dataset.
AI research assistant you control. Run locally for privacy, use any LLM and build your own searchable knowledge base. You own your data and see exactly how it works.
local-deep-research is an open-source project written primarily in Python, with 9.1k stars on GitHub. It was last updated in September 2026.
docker run -d -p 11434:11434 --name ollama ollama/ollamalocal-deep-research vs. the alternatives
All 26 alternatives →| Record | Stars | Pricing | ||
|---|---|---|---|---|
| local-deep-researchthis listing | 9.1k | Python | MIT | Open source |
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| Scrapling | 84k | Python | BSD-3-Clause | Open source |
| TrendRadar | 63k | Python | GPL-3.0 | Open source |
| BettaFish | 42k | Python | GPL-2.0 | Open source |
| khoj | 38k | Python | AGPL-3.0 | Open source |
