5 Best Open-Source NotebookLM Alternatives (2025)

NotebookLM allows you to add PDFs and other documents and engage in AI-powered conversations based on those files. It’s an incredibly useful tool.

However, you might find yourself thinking:

“What if I want to upload unlimited documents?”
“What if I need more diverse podcast voice options?”
“What if I want to integrate my own AI model?”

If you’ve had these thoughts, you’re in the right place.

As of 2025, there are already several open-source alternatives to NotebookLM available under MIT or Apache licenses, allowing you to run your own AI research assistant completely privately. We’ll introduce 5 of them in this article.

What is NotebookLM?

What NotebookLM Offers

NotebookLM is an AI-powered note-taking and research assistant that can be described in one sentence.

1. Document-Based Conversations

NotebookLM is remarkably simple to use. Upload your documents, and within just 3 seconds, you can start having a conversation. The standout feature is the AI-generated podcast, where you can enjoy a 100% AI-generated audio show.

2. Powered by Google’s Gemini

NotebookLM is powered by the Gemini model. While other models like Claude 3.5 Sonnet or Llama can be excellent, the reality is that “which AI is best?” depends entirely on your use case.

3. Completely Free to Use

On top of all these features, it’s completely free. It doesn’t get better than this.

Why Look for Open-Source Alternatives?

1. Data Privacy

With open-source alternatives, you can process your AI data locally. Especially for sensitive business or personal information, this is a crucial advantage.

2. Customization Freedom

Open-source projects with MIT or Apache-2.0 licenses allow you to modify and extend them freely. You can customize features that NotebookLM doesn’t offer to fit your needs.

3. Integration with Your Own AI Models

You can integrate various AI models including OpenAI GPT-4, Anthropic Claude, Meta Llama, or models running on your own PC. You can mix and match Claude, Gemini, or Llama according to your needs.

3 Categories

What types of alternatives exist? They can be broadly categorized into three types.

1. Desktop Solutions

These apps feature a simple GUI and can be easily run locally via Docker. Just run “docker-compose up -d” and you immediately have your own “personal NotebookLM.”

2. Web-Based Solutions

These solutions allow you to install on a server for access from anywhere. Many support both Desktop and Docker deployment, so you can choose based on your needs.

3. Developer-Focused Solutions

These are solutions that allow you to build NotebookLM-like functionality yourself. They support features like Q&A based on documents and podcast creation, but you typically need to write code yourself. They’re suitable for developers who need to build customized services.

Now, let’s introduce the “alternatives you can actually use.”

Top 5 Solutions

AnythingLLM - Desktop Solution

AnythingLLM has gained over 7,600 stars on GitHub. It’s released under the MIT license and specializes in Desktop deployment.

It uses RAG (Retrieval-Augmented Generation) technology. This means the AI finds relevant documents (Retrieval) and generates answers based on them (Generation). It works similarly to NotebookLM but allows you to customize models and settings more freely.

The No-code Agent Builder is particularly noteworthy. You can create workflows like “First summarize the document, then create an outline, then write a blog post” without any coding. All configuration is done through the GUI.

It’s well-suited for individual users or small teams. If you need to ask questions about dozens of internal PDFs or want to run everything on your laptop, this is an excellent choice.

✅ Strengths:

• ✅ Desktop installation takes just 5 minutes

• ✅ Supports RAG + AI agents

• ✅ Compatible with multiple LLMs (OpenAI, Ollama, Anthropic, etc.)

• ✅ MIT license for free customization and extension

❌ Considerations:

• ❌ Requires familiarity with Docker

• ❌ API integration requires separate development (plugin system exists)

4 More Alternatives

The following solutions are primarily designed for Docker deployment and running on servers.

SurfSense - The Power User’s Tool

SurfSense has over 7,600 stars on GitHub. It’s been described as “NotebookLM + Perplexity combined.”

It employs 2-tier RAG technology. While NotebookLM’s RAG is single-tier, SurfSense uses a two-stage retrieval process. This enables more accurate and contextual answers.

Support for over 150 LLMs and 6,000+ embedding models. You can use not only GPT-4, Claude, and Llama but also specialized models like Cohere and Pinecone reranker. You can literally mix and match “GPT-4, Llama embedding, Claude reranking.”

Unlimited podcast creation. While NotebookLM limits you to 3 podcasts in 20 minutes, SurfSense has no such restrictions. Multiple TTS options are available (OpenAI, Azure, Google Vertex AI).

The integration capabilities are impressive. It can retrieve information from services like Slack, Linear, Notion, YouTube, and GitHub for processing. You can create a “company knowledge base” by integrating all your team’s tools.

✅ Strengths:

• ✅ Freedom to choose any LLM/embedding model

• ✅ Unlimited podcast creation (up to 20 minutes)

• ✅ Integration with various productivity tools (Slack, Notion, etc.)

• ✅ Support for 34 languages

• ✅ Open-source, actively developed on GitHub

❌ Considerations:

• ❌ More complex installation than Docker (requires server configuration)

• ❌ Complex API documentation

• ❌ Relatively new project (potential instability)

Open Notebook - The Complete Package

Open Notebook brands itself as “a complete, straightforward NotebookLM alternative.” With over 4,100 stars on GitHub, it’s been featured by major tech media outlets including XDA Developers and ZDNET.

Support for 16+ AI models. You can connect to OpenAI, Anthropic, Google Gemini, Ollama, LM Studio, Mistral, Deepseek, xAI, Groq, and more. Most importantly, all of these can be run locally. You can mix premium models like “Claude, GPT-4, Elevenlabs” as needed.

The podcast feature is highly praised. You can choose from 1-4 speakers, select conversation styles (professional, humorous, enthusiastic) and formats (casual conversation, interview, debate). It’s more flexible than NotebookLM.

Three-pane workflow. You can work simultaneously in three sections: document list, document viewer, and AI chat. This enables quick reference and questioning, making multitasking very smooth.

✅ Strengths:

• ✅ Support for multiple AI providers

• ✅ Customizable podcast creation (style, format options)

• ✅ Easy installation via Docker Compose

• ✅ Active community on GitHub

• ✅ Active Discord community

❌ Considerations:

• ❌ More complex installation than Docker

• ❌ Some features require API key configuration

• ❌ Speed varies depending on model selection (local models can be slow ~1 minute)

LobeChat - The Ultimate UI Experience

LobeChat is “the most beautifully designed AI chat interface.” Released under the Apache-2.0 license, it focuses on delivering an exceptional UI/UX experience.

Note: LobeChat itself is a general AI chat tool. If you want NotebookLM-style document Q&A, you need to visit lobehub.com or configure GitHub integration yourself.

Multimodal support is excellent. You can upload images, videos, and audio files to ask questions. It supports image analysis models like GPT-4V and Gemini Vision. You can upload photos and ask “What building is this?” or “What’s written here?”

MCP (Model Context Protocol) support. This is a protocol that allows AI to access external services. You can connect tools to access APIs, databases, or even web pages directly.

The extensibility is impressive. You can use the OpenAI API directly or integrate with locally running Ollama models.

There’s a plugin marketplace. You can install various plugins to extend functionality. For instance, you can add web search or document creation features.

✅ Strengths:

• ✅ Beautiful and intuitive UI

• ✅ Multimodal support (images, videos, audio)

• ✅ Integration with various productivity tools (calendar, task management, etc.)

• ✅ MCP support

• ✅ Apache-2.0 license for 100% customization

❌ Considerations:

• ❌ Requires separate configuration for Docker or Vercel deployment (relatively easy)

• ❌ API integration requires separate development

• ❌ RAG functionality requires additional configuration

NotebookLlama - For Developers Using LlamaIndex

NotebookLlama is built by LlamaIndex. If you’re already familiar with LlamaIndex, it’s worth checking out.

LlamaCloud integration. You can easily upload and process documents using LlamaCloud. Supports parsing various file types including spreadsheets, PDFs, and more.

Postgres + Jaeger for observability via Docker Compose. It stores conversation history (Postgres) and tracks system performance (Jaeger), making it easy to monitor “how is my AI performing?” Everything can be set up with Docker Compose.

MCP + Streamlit for easy GUI. It leverages MCP protocols and builds the UI with Streamlit. It’s a simple design typical of Python-based tools.

✅ Strengths:

• ✅ Tight integration with LlamaIndex

• ✅ Support for monitoring and observability (DB, tracing)

• ✅ Suitable for Python developers

• ✅ Active development and continuous improvements on GitHub

❌ Considerations:

• ❌ High technical entry barrier for those unfamiliar with LlamaIndex

• ❌ More complex LLM configuration compared to other alternatives

• ❌ LlamaCloud may incur separate costs

Comparison Table: 5 Alternatives at a Glance

Which solution should you choose? Here’s our recommendation.

Open Notebook is recommended if you simply want to upload PDFs and ask “What’s this about?” or “What’s the difference between A and B?”. With 16 AI model options and an intuitive UI, it’s the most accessible option.

SurfSense is ideal for those who want to do more. If you want to integrate company-wide data, analyze Slack conversations and Notion documents comprehensively, or ask “What did we discuss this week about this topic?”, this is your best choice. The 2-tier RAG technology extracts only the most relevant information, allowing you to work with data from various sources simultaneously.

AnythingLLM excels in ease of use. The Desktop version can be set up in 10 minutes. With an MIT license, you can freely modify and extend it. If you want to start quickly without complex server setup, this is the way to go.

LobeChat stands out if UI is important to you. If you frequently think “This tool looks outdated” or “I wish the interface was prettier,” LobeChat is worth trying. The beautiful UI enhances the overall user experience.

Conclusion - Which One to Choose?

NotebookLM is an outstanding tool. However, it has limitations such as restricted customization, potential privacy concerns, limited integration options, and dependency on Google’s infrastructure.

The alternatives we’ve introduced today complement these shortcomings. They allow you to choose your AI models, offer advanced RAG technology, provide beautiful UIs, and maintain full control over your data. Additionally, they’re all completely free to use.

All 5 solutions are released under MIT or Apache-2.0 licenses. This means commercial use is permitted, and they can be modified and extended freely. All source code is publicly available on GitHub.

There’s no “best” solution. Choose NotebookLM if you want simplicity and free access, or opt for open-source alternatives if you need customization and control.

Try out these 5 alternatives. You can find more in-depth reviews and comparison posts on Reddit communities like r/LocalLLaMA and r/selfhosted.

Prefer Simpler Solutions?

If you’re thinking “This seems too technical, I just want to use it like NotebookLM,” there’s a solution for you.

LocalDocs offers a 100% local alternative to NotebookLM. Everything runs on your PC without an internet connection, so your data never leaves your device. It’s incredibly easy to install and use.

It’s perfect for those who want to start immediately. Utilize AI tools while maintaining complete data privacy.

References:

1. AFFiNE - 2025 Top NotebookLM Alternatives to Elevate Your Research

2. Nut Studio - Best NotebookLM Alternatives [2025]: From Cloud to Open-Source Options

3. GitHub - SurfSense: Open Source Alternative to NotebookLM

4. XDA Developers - I replaced NotebookLM with a self-hosted alternative

5. Daily Dose of DS - Building an Open NotebookLM Clone (Hands-on)

6. ZDNET - I found an open-source NotebookLM alternative that’s powerful, private, and free

7. It’s FOSS - An Open Source Alternative to Google’s NotebookLM

8. GitHub - Open Notebook by lfnovo

9. HackerNoon - 6 Best NotebookLM Alternatives in 2025

10. Saner.AI - NotebookLM Alternatives: We tested the best 10 in 2025