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Refactoring title and added proper image

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Daniel Ching 2025-08-04 18:03:16 +08:00
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@ -4,13 +4,13 @@ description: "A simple guide to running replicating Deep Research results for fr
tags: AI, local models, Jan, GGUF, Deep Research, local AI tags: AI, local models, Jan, GGUF, Deep Research, local AI
categories: guides categories: guides
date: 2025-08-04 date: 2025-08-04
ogImage: assets/ ogImage: _assets/research-result-local.png
twitter: twitter:
card: summary_large_image card: summary_large_image
site: "@jandotai" site: "@jandotai"
title: "Replicating Deep Research with Jan" title: "Replicating Deep Research with Jan"
description: "Learn how to replicate Deep Research results with Jan." description: "Learn how to replicate Deep Research results with Jan."
image: assets/ image: _assets/research-result-local.jpg
--- ---
import { Callout } from 'nextra/components' import { Callout } from 'nextra/components'
@ -18,7 +18,7 @@ import CTABlog from '@/components/Blog/CTA'
# Replicating Deep Research in Jan # Replicating Deep Research in Jan
Ever wondered how OpenAI’s Deep Research works? Since the release of Deep Research in February this year, it has been lauded as a tool that is able to “output thorough research”. Ever wondered how OpenAI’s Deep Research works? Since the release of Deep Research in February 2025, it has been lauded as a tool that is able to “output thorough research”.
There are two core features of Deep Research: There are two core features of Deep Research:
@ -32,10 +32,7 @@ While the outputs of deep research might be mind blowing at first glance, it is
Deep Research, at a high level, is essentially a pipeline / tool chain through which a user would go through. The inner workings of this pipeline might vary from provider to provider, but we’ve done up a table for you to compare the results below. Deep Research, at a high level, is essentially a pipeline / tool chain through which a user would go through. The inner workings of this pipeline might vary from provider to provider, but we’ve done up a table for you to compare the results below.
At a high level, the pipeline would look something like this: At a high level, the pipeline would look something like this:
![Deep Research Flow Excalidraw](./_assets/deepresearch-flow.png)
```
user enters query → (optional) clarifying question through a smaller model → (optional) original query is appended to follow up response → response parsed through larger `deep-research` model → output
```
The crux of Deep Research lies in the pipeline’s ability to output a substantiated report which has cited information from a variety of sources. The crux of Deep Research lies in the pipeline’s ability to output a substantiated report which has cited information from a variety of sources.
<Callout type="info"> <Callout type="info">