I’ve been using NotebookLM for months. It’s my go-to for work research, and I’ve used it for everything from planning weekly meals to understanding bulky documents I don’t have the time to read on my own.
But the more personal stuff I fed it, the more I started reaching limits that had nothing to do with the quality of its responses.
AnythingLLM fixed most of those problems, and it runs right on my Android phone.
NotebookLM’s limits caught up with me
A great tool with some real constraints
NotebookLM’s free tier gives you 100 notebooks with up to 50 sources each, 50 chat queries per day, and 3 audio overview generations.
Those numbers are fine for casual work, but I used up 50 queries faster than I expected on days when I was actively cross-referencing documents or asking follow-up questions.
The bigger issue for me was that NotebookLM requires an internet connection for everything. It runs on Gemini, and there’s no offline mode on any tier.
I often work in places where connectivity is unreliable, so having my research tool unusable when I need it most is frustrating.
I also wanted more control over which AI model I was using. NotebookLM locks you into Gemini, which is strong for general tasks, but I sometimes want a different model for specific kinds of analysis.
While I wouldn’t use NotebookLM to replace OneNote and Evernote, I still use it for Workspace tasks and professional research. But for personal projects, I need something with fewer restrictions.
I can’t stop thinking about how much easier college would’ve been with NotebookLM
NotebookLM is the best study partner you could have
AnythingLLM runs entirely on my phone
No account, online cloud, or usage limits
AnythingLLM is a free, open source AI app built by Mintplex Labs, and its Android app is what made me switch to it for personal use.
I downloaded it from the Google Play Store, picked one of its pre-selected on-device models, and started chatting with my documents within minutes.
There’s no sign-up or Google account required, and my data never leaves my phone.
The app runs a small language model and a local vector database directly on-device, which means I can upload PDFs and notes and get responses from my own sources entirely offline.
AnythingLLM calls this on-device RAG, and it works well enough that I’ve used it on flights and in areas with no signal at all.
I can swap models whenever I want
Gemini is good, but options are better
On the Android app, I can switch between on-device models depending on what I’m doing. This feature keeps me on AnythingLLM for anything beyond simple document summaries.
The pre-selected models that ship with the app are optimized for mobile performance, so they run smoothly even on mid-range hardware.
If I need something more powerful than what my phone can handle locally, AnythingLLM lets me connect to cloud-based models from providers like OpenAI, Anthropic, or Groq using my own API keys.
I’ve done this a handful of times when I needed stronger reasoning on a complex document, and the setup was painless. I’m not against using a cloud provider, but I like having the choice to do so.
AnythingLLM is even more flexible when combined with the desktop app. I can connect to Ollama and run larger open source models locally on my PC, then sync those workspaces to my phone over my local network.
That sync feature is opt-in, and nothing is uploaded to external servers in the process.
I thought Gemini was enough until I finally tried Claude
I ignored Claude for months, and now I get the hype
My personal files stay on my hardware
Privacy that doesn’t require trust in a third party
Google is upfront that NotebookLM doesn’t use uploaded documents to train its AI models. For Workspace users, the Cloud Data Processing Addendum adds extra protections, and I trust that for work.
However, the journal entries, rough ideas, and half-formed opinions I started uploading were things I wouldn’t store in a Google Docs file.
There’s an architectural difference between NotebookLM and AnythingLLM. With the latter, there’s no server receiving my files, no cloud infrastructure holding my data, and no privacy policy I need to read to understand what’s happening with my uploads.
The project is MIT-licensed, actively maintained, and has over 54,000 stars on GitHub with more than 400 contributors.
Mintplex Labs is transparent about how the app works, and the open source codebase means anyone can verify its privacy claims.
What I still miss about NotebookLM
Audio overviews are hard to replace
NotebookLM’s audio overviews are the one feature I miss enough to mention. I use them constantly to absorb research while doing other things, and AnythingLLM has no equivalent.
For now, I’m reading everything instead of listening to it, and that’s honestly a noticeable decrease in convenience.
AnythingLLM’s Android app is still early compared to its desktop version. It only supports a curated set of small on-device models, and features like custom MCP integrations require syncing with the desktop app.
Response quality also depends on your phone’s processor, and I noticed slower, less detailed answers on mobile compared to running larger models on my PC through Ollama.
I’m keeping both, but for different things
I haven’t replaced NotebookLM entirely. It’s still where I do work research, and its recent updates keep making it better for that purpose.
AnythingLLM is where my personal projects live now, running on my phone with no limits or cloud dependency and a model I can swap out whenever I want.
If you’re reaching NotebookLM’s free-tier caps, or want your private documents to stay private, it’s the best Android alternative I’ve found.
