PageGrok vs Page Assist: Which Local AI Extension to Choose
If you are looking for a Chrome extension that connects local AI models to your browser, you have probably found both PageGrok and Page Assist. Both are open-source, both work with Ollama, and both are free. So which one should you use?
This is an honest comparison. We will be clear about where Page Assist is stronger.
At a glance
| PageGrok | Page Assist | |
|---|---|---|
| Primary focus | Read and understand the current webpage | General-purpose local AI chat |
| Page content extraction | Automatic — reads the DOM when you open the panel | Manual — paste content or use RAG features |
| Model support | Ollama (auto-discovery), OpenAI-compatible APIs | Ollama, Chrome AI (Gemini Nano), multiple providers |
| Setup complexity | Install → works (Ollama auto-detected) | Install → configure provider and model |
| Chat history | Per-page, transient | Persistent across sessions |
| UI approach | Minimal side panel, focused on Q&A about current page | Full chat interface with multiple features |
| Open source | Yes | Yes |
| Price | Free | Free |
Where PageGrok is stronger
Built for webpage reading
PageGrok does one thing: it reads the page you are on and lets you ask questions about it. When you open the panel, it automatically extracts the page text (walking the DOM including Shadow DOM), sends it to your local model, and gives you a focused conversation about that content.
You do not paste text, configure RAG pipelines, or manage chat sessions. Open page, ask question, get answer.
Zero-configuration Ollama connection
If Ollama is running, PageGrok finds it. No endpoint configuration, no model selection dialogs on first run. It queries 127.0.0.1:11434/api/tags and populates the model list automatically.
Privacy by architecture
PageGrok has no cloud features, no account system, no telemetry that sends content anywhere. The extension talks exclusively to localhost (or a self-hosted endpoint you configure). Page content stays in the browser → local model pipeline.
Where Page Assist is stronger
More providers and flexibility
Page Assist supports Chrome’s built-in AI (Gemini Nano), multiple OpenAI-compatible endpoints, and various model providers. If you need to switch between cloud and local models, or want to use Chrome’s native AI capabilities, Page Assist has more options.
Persistent chat history
Page Assist keeps your conversation history across sessions. If you want to refer back to previous chats, this is valuable. PageGrok treats each page as a fresh context — when you navigate away, the conversation is done.
Broader feature set
Page Assist includes features beyond page reading: web search integration, RAG capabilities, and general-purpose chat. If you want a local AI assistant that does more than webpage Q&A, Page Assist covers more ground.
When to choose PageGrok
- You primarily want to ask questions about webpages you are reading
- You value zero-setup — install and it works with Ollama
- You want the simplest possible interface — no feature overwhelm
- Privacy is non-negotiable — no cloud, no accounts, no content leaving your machine
- You read lots of developer docs, news articles, or technical content and want quick answers
When to choose Page Assist
- You want a general-purpose chat that can also reference pages
- You need persistent chat history across sessions
- You want to use Chrome AI (Gemini Nano) or multiple cloud providers
- You prefer a feature-rich interface with RAG, web search, and more
- You use multiple AI providers and want one extension for all of them
Can you use both?
Yes. They install independently and do not conflict. A reasonable setup: use PageGrok for quick page-specific questions while reading, and Page Assist for longer conversations or tasks that are not tied to a specific page.
Setup comparison
PageGrok setup
- Install Ollama and pull a model
- Install PageGrok from Chrome Web Store
- Done — models appear automatically
Page Assist setup
- Install Ollama (or another provider)
- Install Page Assist from Chrome Web Store
- Open settings, select provider
- Configure model and endpoint
- Ready to use
Summary
PageGrok is laser-focused on one job: reading webpages with local AI. It does that job with minimal setup and maximum privacy. Page Assist is a broader tool that does many things well but requires more configuration.
If your main use case is “I want to ask questions about the page I am looking at, using a local model, with zero friction” — PageGrok is built for exactly that.
If you want a Swiss Army knife local AI assistant in your browser — Page Assist may be the better fit.
FAQ
Is PageGrok a fork of Page Assist?
No. PageGrok and Page Assist are independent projects with different codebases. They solve a similar problem — connecting local models to a browser — but take different design approaches.
Can I use both at the same time?
Yes. Both extensions can be installed simultaneously. They do not conflict because each has its own browser action button and settings. You might use one for page reading and the other for general chat.
Which is better for reading long pages?
PageGrok is purpose-built for reading webpages. It extracts page content automatically and focuses the model on what you are currently viewing. Page Assist provides a general-purpose chat where you can paste or reference page content manually.
Are both free?
Yes. Both are free extensions that work with local models. Neither charges subscription fees or per-query costs. Your only expense is the hardware running the model.
Try it on the page you are reading right now
PageGrok connects your local models to any browser tab. Free, private, no sign-up.
Related guides
- Local AI in the Browser: Run Ollama and Chat With Any Webpage — Connect local models from Ollama, LM Studio, or oMLX to the page you are reading. Setup, model recommendations, real limits, and guides for specific reading tasks.
- Connect Ollama to Your Browser: Setup & CORS Fix — Step-by-step guide to connect Ollama to a Chrome extension. Covers installation, CORS configuration with OLLAMA_ORIGINS, and common connection errors.