Otter vs Fireflies vs Granola: I've Only Actually Used One of Them

I went looking for an honest comparison of AI meeting notetakers a few weeks ago and could not find one. What I found instead was a dozen articles rating five tools out of ten on "accuracy" and "ease of use", none of which mentioned a single real call any of the writers had actually recorded. So here is mine, with the bit those articles leave out stated up front: I have run one of these tools on every call I take for six weeks. I have not run the other two. Everything below is labelled accordingly.

That distinction matters more in this category than in most, because a notetaker is only tested by the things that go wrong on a real call — three people talking over each other, someone reading a figure out loud, a client hedging in a way that a summary flattens into a decision. None of that shows up in a feature table. It only shows up after a few weeks of trusting the output and then discovering where it let you down.

What I can tell you first-hand: six weeks of Otter.ai

I picked Otter.ai because it joins Zoom and Google Meet without anyone on the other end installing anything, and I have had it on every sponsor call, brief and planning chat since. I wrote up the full six weeks separately, but the short version is that the transcription itself was rarely the problem. It is genuinely good at the boring, reliable jobs: finding the exact date someone promised a file, catching a URL read out loud, giving you something searchable weeks later when you cannot remember which call a detail came from.

Where it fell down was subtler and, I suspect, common to the whole category rather than specific to Otter. On three-person calls the speaker labels drifted often enough that I stopped trusting them without checking. On one call a sponsor's figure came through slightly wrong in the export — close enough that I would have believed it if I had not happened to remember the real number. And the auto-summary once turned a client's genuinely hesitant "let me think about it and come back to you" into a tidy bullet that read as agreement. Nothing lied. The software just prefers a clean sentence to an uncertain one.

The other thing worth saying, because it is the sort of detail a feature table cannot carry: transcript quality is downstream of microphone quality. Part of why my transcripts got better was nothing to do with the software at all — I had gone back to a wired headset for these calls, and a clean mic feed does more for accuracy than any setting in the app.

What Otter costs

Otter's own pricing page currently lists a free Basic plan with 300 transcription minutes a month, Pro at $16.99 per user per month or $8.33 billed annually with 1,200 minutes, and Business at $30 per user per month or $19.99 billed annually with unlimited minutes. Those are US dollar figures taken from the vendor at the time of writing, and this is a category where pricing moves — read the page before you commit.

The free tier is more useful than 300 minutes sounds if your calls are short, and less useful than it sounds if you take a lot of hour-long ones. Five hour-long calls will exhaust it.

What I have only researched: Fireflies and Granola

Here is the honest boundary. I have read the documentation and the pricing pages for both of these. I have not run either on a real client call, so I am not going to tell you how their summaries hold up when a conversation gets messy, because I do not know.

Fireflies is the closest direct competitor to Otter in shape — a bot that joins the call, transcribes it, and gives you a searchable archive plus an assistant you can question about past meetings. Its listed pricing is Free at $0, Pro at $18 per user per month or $10 billed annually, Business at $29 or $19 billed annually, and Enterprise at $39 per seat billed annually only. On the headline paid tiers it undercuts Otter's monthly pricing and costs slightly more than Otter's annual Pro.

Granola works differently enough that it is not really the same product. Rather than sending a bot into the meeting, it listens on your own machine and augments notes you are typing yourself — which, given what six weeks of Otter taught me about handing over my attention, is a design I am genuinely curious about. It lists a free Basic plan with limited meeting history, Business at $14 per user per month, and Enterprise at $35.

Otter vs Granola: the one difference that actually decides it

Those two get searched against each other constantly, and almost every answer I found treats it as a quality question. It is not. On the evidence above it is a question about shape, and the shape is the thing you should be choosing between.

Otter sends a bot into the call and hands you a transcript and a searchable archive you did not have to write. Granola does the opposite: it listens on your own machine and improves notes you are still typing yourself. So the real question is not which summarises better — it is whether you want to stop taking notes, or keep taking them and have them tidied up. Fireflies sits on Otter's side of that line, which is why "Fireflies vs Granola" is the same question again with different pricing.

Two consequences worth knowing before you pick. A bot that joins the call is visible to everyone in the room, and a tool listening locally is not — so with Granola the job of telling people they are being recorded falls entirely to you, and it still needs doing. And on the listed prices above, Granola's Business tier at $14 per user per month undercuts both Otter Pro at $16.99 and Fireflies Pro at $18 monthly, so cost is not the tie-breaker people expect it to be.

Given what six weeks of Otter taught me about how much of a conversation I was willing to stop listening to, Granola's design is the one I would test next. That is a statement about which bet I would place, not about which tool is better — I have run one of these on real calls and not the other, and I am not going to blur that line.

The option most people are already paying for

Before adding a second subscription, check whether the one you have already covers this. Zoom's AI Companion is included at no additional cost with paid Zoom user accounts and will summarise the meeting and pull out action items — Zoom is explicit that free accounts do not get it, including free users inside a paid organisation. Teams and Google Meet have equivalents attached to their paid tiers.

The trade-off is the one I described in the article above: a built-in tool is tidier if every call you take lives inside that platform, and useless the moment a client sends you a Meet link instead. A standalone tool follows you across all of them and gives you one searchable archive. That is genuinely the main reason I pay for one, and if all my calls were in Zoom I probably would not.

"After six weeks I stopped asking which notetaker was most accurate and started asking how much of the call I was willing to stop paying attention to. That question has a better answer, and it is the same one whichever tool you pick."

The comparison nobody runs

Every one of these tools will transcribe a call well enough. The variable that actually changed my outcomes was not the software — it was how much I let it be responsible for. I am back to writing three or four bullets by hand on every call: the outcome, the next step, anything with a number attached. Not because my notes beat the transcript on accuracy, but because writing them is what keeps me in the room.

What happens to the notes afterwards matters more than which tool produced them, too. A transcript that nobody re-reads is an archive, not a system. Mine get pulled into a project workspace where the context actually accumulates — I wrote up how I taught a Claude project my business for exactly that reason, and it does far more for me than any difference between these three products would. If you want the whole pipeline rather than the tool choice, the step-by-step meeting notes workflow is here.

What I would actually do this week

Run the free tier of one tool on your next five calls and read the transcripts against your own memory of what was said — that comparison, on your calls, will tell you more in a week than any article can, this one included. Pay attention less to whether the words are right and more to whether the summary preserved the uncertainty in the conversation, because that is where I got caught.

If you are setting this up for client work rather than internal calls, the accuracy of the record starts to carry real commercial weight, and it is worth being deliberate about the whole process rather than trusting a default. That is a chunk of what I end up untangling for people on the consulting side of this site.

The same question — how far do you trust a machine transcript — turns up in editing as well as note-taking. I now cut my videos by editing their transcript rather than a timeline, which only works if the text is right in the first place.

Questions people actually ask

Otter vs Granola: which should I pick?

Pick on shape, not on which one writes a better paragraph. Otter puts a bot in the call and gives you a transcript plus a searchable archive without you typing anything; Granola listens on your own machine and improves notes you are still writing yourself. If the outcome you want is to stop taking notes, that is Otter. If you want to keep taking them and have them cleaned up, that is Granola. On the listed prices Granola's Business tier at $14 per user per month is the cheaper of the two. I have used Otter for six weeks and have not run Granola on a real call, so take the comparison as structural rather than first-hand.

What is the difference between Fireflies and Granola?

They are not really the same kind of product. Fireflies is Otter-shaped — a bot joins the meeting, transcribes it, and gives you a searchable archive plus an assistant you can question about past calls. Granola sends no bot: it listens locally and augments notes you type yourself. Because nobody else on the call can see a local listener, telling people they are being recorded is on you. Listed pricing is Fireflies Pro at $18 per user per month (or $10 billed annually) against Granola Business at $14. I have run neither on a real client call, so this is drawn from their own documentation and pricing pages, not from use.

Which AI meeting notes tool is best?

I can only answer that honestly for one of them, which is rather the point of this piece. I have run Otter.ai on every call for six weeks and it does the job well, so it is the one I can actually recommend from use. Fireflies and Granola may well be better for you — I have read their documentation and their pricing pages, and I have not run either on a real client call, so anything I said about how they feel in practice would be invented. Be wary of any comparison that rates five tools out of ten on "accuracy" without saying which calls were recorded.

How much does Otter.ai cost?

At the time of writing Otter lists a free Basic plan with 300 transcription minutes a month, Pro at $16.99 per user per month or $8.33 billed annually with 1,200 minutes, and Business at $30 per user per month or $19.99 billed annually with unlimited minutes. Those are the figures on Otter's own pricing page in US dollars, and vendors change them often — check the page before you commit to a plan.

Do I need a paid AI notetaker at all?

Quite possibly not. If your calls already happen in Zoom on a paid plan, Zoom's own AI Companion is included at no extra cost and produces a summary and action items without another subscription — Zoom is explicit that free accounts do not get it. Microsoft Teams and Google Meet have equivalents attached to their paid tiers. Try the one you are already paying for before you add a second bill.

Is a free AI notetaker plan enough for one person?

For a handful of calls a month, usually yes. Free tiers are where the vendors are least consistent, though: while checking figures for this article I found two pages on Fireflies' own site giving different storage limits for its free plan, and its knowledge-base pricing article did not state a limit at all. I could not settle it, so I am not going to quote a number — open the vendor's pricing page and read the free column yourself before you plan around it.

Does an AI notetaker make you worse at listening?

It did for me, and that was the finding that surprised me most across six weeks of running one. Knowing the transcript existed, I stopped taking my own notes, and stopped holding the shape of the conversation in my head along with them. The fix was not a different tool — it was writing three or four bullet points by hand on every call anyway and treating the transcript as a backup rather than the record.