local-deep-research

~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.…

Local Deep Research AI powered research assistant for deep, agentic 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 It has reached 7,955 GitHub stars, written primarily in Python.

Why now: Recent coverage — "AlphaSignal AI (@alphasignal.ai) on Threads" — alongside renewed developer interest is driving current visibility.

• 7,955 GitHub stars, 694 forks — verifiable at github.com/LearningCircuit/local-deep-research.
• Primary language Python; topics: academia, anthropic, arxiv, brave.
• Licensed MIT.
• Third-party coverage: "AlphaSignal AI (@alphasignal.ai) on Threads".

Considerations: Solid adoption (7,955 stars) but quiet cross-source signal right now — established utility more than a current breakout.

EARLY MOMENTUM · Research: Adoption is real but cross-source confirmation is thin — a short hands-on trial (Python) will tell you more than the metrics.

Sources: LearningCircuit/local-deep-research on GitHub · AlphaSignal AI (@alphasignal.ai) on Threads · LearningCircuit/local-deep-research — GitHub trending ... - Trendshift · Local Deep Research Achieves 95% on SimpleQA Benchmark