# 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.

## Facts
- **Category:** [Research & Data Agents](https://agentsearchengine.app/category/research-agents)
- **Type:** Agent
- **Pricing:** Open source
- **GitHub stars:** 8,835
- **Language:** Python
- **License:** MIT
- **Last repo activity:** today (Aug 3, 2026)
- **Source code:** https://github.com/LearningCircuit/local-deep-research
- **Listing on Agent Search Engine:** https://agentsearchengine.app/agents/local-deep-research
- **Data verified:** July 2026

## 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.

_From the project's README._

## Install

```
docker run -d -p 11434:11434 --name ollama ollama/ollama
```

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