NotebookLM has become my default research and learning companion, but it’s never been a real note-taking app. Gistr, on the other hand, positions itself as exactly that. It has block-based note-taking features, as well as more powerful YouTube transcript handling, while still offering AI on top. That’s why it’s a viable alternative for anyone who doesn’t want to commit to Google’s NotebookLM.

However, NotebookLM, which uses Gemini 2.5, still sports superior synthesizing and retrieval abilities. I’d already spent time pitting them against each other and comparing their features and workflows. So instead of overthinking which one to commit to, I thought, why not use them together? It turned out to be a pretty genius move for my productivity…

What is Gistr?

A quick rundown of NotebookLM’s biggest rival

I’ve covered Gistr extensively already here at XDA, but in short: it’s an AI-native smart notebook that pretty much does what NotebookLM does. Except, Gistr has a couple of extras that NotebookLM lacks, such as folder organization and note blocks. You can upload documents, links, and YouTube videos, and the AI can extract and resynthesize the content according to your prompts. So you can get summaries, insights, etc., and you can also create your own notes alongside the AI’s responses.

Gistr’s strengths

Where it outperforms NotebookLM

Gistr has a leg up on NotebookLM in several areas. For starters, it comes with real organization features that let you sort your threads into collections, and it’s a lot more flexible than NotebookLM’s rigid notebook system. It also has superior YouTube transcript analyzing capabilities with transcript-specific features such as Highlights and Moments.

As mentioned, Gistr is a proper note-taking app with a bunch of formatting options such as headers, lists, code blocks, and image inserts. And all of it blends with your prompts and the AI’s responses - NotebookLM’s one tiny Note feature pales in comparison. Last but not least, you can actually export your threads as PDF or Markdown files, which is not something you can do in NotebookLM (you can only export your notes to Docs and Sheets).

In a way, this makes Gistr more practical than NotebookLM. But rather than replacing one with the other, I think it makes more sense to use it alongside NotebookLM to cover its gaps.

NotebookLM’s strengths

It’s still the best AI research assistant out there

Although Gistr has a decent AI chatbot, nothing compares to NotebookLM’s synthesizing capabilities. Built on the Gemini 1.5 architecture, and now using Gemini 2.5, it excels at pulling patterns across multiple sources, surfacing connections you didn’t explicitly ask for, and retaining long-range context. Where Gistr is better as a structured notes app, NotebookLM shines when you’re trying to understand complex subjects or even messy documents. It’s the tool to reach for if you want responses in plain language that still preserve nuance.

Furthermore, NotebookLM has its Studio panel, which is a suite of generative features that transform your sources into different formats. It includes things like the Audio Overview, Video Overview, Mind Map, Flashcards, Quiz, and the more recent Slide Deck. NotebookLM actively reshapes your content to improve understanding and recall.

Using NotebookLM and Gistr together

Combining their strengths

So how do I actually use NotebookLM and Gistr together when they’re built by completely different companies with different priorities? That’s exactly why they work well together, because where one falls short, the other picks up. The key here is in Gistr’s export features. Just like most of the other tools I pair with NotebookLM, I do it by exporting the notes to a local folder that’s synced to Drive, which I can fetch directly from within NotebookLM thanks to its Drive integration.

My work starts in Gistr. I use its organization features to sort my sources into neat categories to begin with. Whether I’m working with a YouTube video, web link, or document, I’ll start creating highlights of the content right away. One of the things I like most about Gistr is the prompt recommendations - the app even sections them off into categories, which takes it a step further than NotebookLM’s recs. Once I’ve got my responses, I’ll edit them and add my own notes as well, effectively building out my threads into full-fledged notebooks.

After populating my threads with note blocks, I export them to one of my local folders on Windows that’s synced with my Google Drive. Gistr lets you download your threads as PDF files, Markdown files, and images - NotebookLM can only fetch PDF and Doc files from your Drive at this moment. Once my Gistr files are in Drive, I head over to NotebookLM and search for them to add as sources. From there, it’s just a matter of letting NotebookLM do what it’s best at - helping me understand things and learn faster.

Since there is no way to locally export your NotebookLM notebooks, I just send them over to Google Docs, from where I can export in PDF, and I can then feed those files back into Gistr. Keeping the loop going this way takes a bit of manual labor, so I admittedly usually stop at NotebookLM. But beyond this one inconvenience, it's been a great pairing for staying on top of my design studies and projects.

I don’t have to choose one or the other

Gistr is a great replacement for anyone who is looking for an alternative. However, I don’t see myself leaving NotebookLM completely anytime soon. Instead of overthinking which one is better, using them together has been far more effective. Gistr handles structured note-taking and highly-specific prompt formulations, plus it lets me get those documents into my local stack. NotebookLM then does the heavy-lifting; it excels at synthesis and retrieval. And together, they cover each other’s blind spots better than I'd expected.