August 19, 2026 · By The Listently Team
Listently vs TurboScribe vs Otter.ai: A Real Comparison
If you’re uploading recorded audio or video files and you care about what happens to them afterwards, Listently is the closest fit — it deletes uploaded audio immediately after processing, supports over 100 languages, and costs $8.99/mo billed annually. TurboScribe is built around the same upload-and-transcribe workflow and is worth a look if you process very large batches — its per-batch limit is higher than Listently’s. Otter.ai is a different product wearing similar clothes: it’s strongest when it joins your live meetings and weakest when you just want to hand it a file. Pick based on where your audio comes from, not on feature-count comparisons.
The short version
| Listently | TurboScribe | Otter.ai | |
|---|---|---|---|
| Primary workflow | Upload files | Upload files | Live meeting capture |
| Free tier | 3 transcriptions/day, 30 min per file | 3 transcriptions/day, 30 min per file | 300 min/month, live meetings |
| Paid entry price | $8.99/mo annually, $13.99/mo monthly | $10/mo annually, $20/mo monthly | $8.33/mo annually, $16.99/mo monthly |
| Languages | 100+ | ~100 | English plus a small set of others |
| Speaker labels | Automatic, renameable everywhere | Automatic | Automatic, plus voice matching over time |
| Batch upload (paid tier) | Up to 10 files at once | Up to 50 files at once | Not applicable — live capture |
| Audio retention | Deleted immediately after processing | Stored until you delete it | Stored |
Pricing on all three changes over time — the numbers above reflect what’s published as of this writing, so double-check current pricing on each site before committing to an annual plan.
Free tiers: what you actually get
Free tiers are where these three diverge most sharply, and it’s worth understanding the shape of each limit rather than just the headline number.
Listently’s free plan
Three transcriptions per day, up to 30 minutes per file, with uploads up to 2GB. The daily reset matters more than it sounds: if you’re transcribing one interview a day or a couple of lecture recordings, you may simply never hit the ceiling. The 30-minute cap is the real constraint — a two-hour panel discussion won’t go through on free.
TurboScribe’s free plan
Also three transcriptions per day, capped at 30 minutes per file — the same length cap as Listently’s free plan. Same daily-reset logic, so the practical question is again whether your files are short enough to fit under the cap. If your typical recording runs past 30 minutes, neither free tier gets you through it, and the decision comes down to the paid plans instead.
Otter.ai’s free plan
Otter allocates a monthly minute budget (300 minutes/month on the free Basic plan) rather than a daily transcription count, plus a per-conversation length limit — and this is the part people trip over: it’s built for recording meetings live inside Otter, not for uploading a backlog of files you already have. If you arrive with a folder of MP3s, that 300-minute pool empties fast.
Paid pricing, compared honestly
Listently Pro is $8.99/mo billed annually or $13.99/mo billed monthly, and removes the file-length limit entirely while lifting uploads to 5GB and transcriptions to unlimited. There’s no per-minute meter to watch.
TurboScribe’s Unlimited plan is $10/mo billed annually ($120/yr) or $20/mo billed monthly — no minute quotas once you’re on it. It’s the closest structural comparison to Listently Pro — both sell “stop counting” rather than a minute allowance.
Otter’s paid tiers are metered. Pro is $8.33/mo annually ($16.99/mo monthly) with a 1,200-minute monthly cap, and Business steps up to $19.99/mo annually ($30/mo monthly, 5-seat minimum) with a 6,000-minute-per-user cap. That model makes sense for a team standardising on Otter for meetings; it makes less sense if you’re one person with a hundred hours of archived audio and no interest in a per-minute ceiling.
The practical takeaway: if your volume is unpredictable, unmetered plans remove a category of anxiety that metered plans don’t.
Speaker detection and how usable the labels are
All three detect speakers automatically. The difference is what you can do with the output.
Listently labels speakers automatically and lets you rename them to real names after the fact — and the rename propagates everywhere, including into the AI summary. That last part is the bit that saves time. Renaming “Speaker 2” to “Dr. Reyes” in a transcript is useful; having the summary then read “Dr. Reyes raised the funding timeline” instead of “Speaker 2 raised the funding timeline” is what makes the document shareable without a second editing pass. The transcript text itself is editable after transcription completes, so you can fix names and misheard terms in the same sitting.
TurboScribe produces speaker-separated transcripts on the same automatic-diarization principle.
Otter has an advantage here in one specific scenario: because it’s designed around recurring meetings with the same people, it can learn voices over time and apply names automatically across future sessions. If you run the same weekly standup with the same six people, that’s genuinely less work. If every recording has different participants — interviews, field research, one-off client calls — the advantage disappears.
Language support
This is the least ambiguous comparison of the three.
Listently supports over 100 languages. TurboScribe is in a similar range. Otter.ai supports English plus a much smaller set of additional languages, and its feature depth is clearly strongest in English.
If any part of your work involves non-English audio — multilingual interviews, international research, foreign-language podcast sourcing — Otter is likely off the table regardless of how good its meeting features are. Language support isn’t a nice-to-have you can work around; either the tool handles your audio or it doesn’t.
Privacy stance
Read the actual policies rather than the marketing page, because the differences here are substantive.
Listently states that audio and transcripts are never used to train any AI model and are never shared with third parties, and that uploaded audio is deleted immediately after processing. The transcript stays in your account; the source file doesn’t linger on a server.
TurboScribe also states it doesn’t train models on user content, but files remain stored in your workspace until you delete them yourself.
Otter’s model involves retaining recordings and transcripts as part of how the product works — voice matching across meetings requires stored voice data, by definition. Its privacy policy states that de-identified, aggregated usage data may be used to maintain and improve its products. That’s not unusual for the category, but it’s a meaningfully different posture from immediate deletion, and it matters if you’re handling confidential interviews, legal material, medical discussions, or anything under a research ethics approval. Read the current policy on Otter’s own site before relying on this comparison for a compliance decision.
Summaries: useful or generated filler
All three generate AI summaries. The failure mode to watch for is a summary that invents action items nobody agreed to, which is worse than no summary because it reads confidently.
Listently generates its summary from the actual transcript text, attributes points to specific speakers, and is explicitly instructed not to invent action items or conclusions that aren’t present in the recording. Combined with speaker renaming, the output is a summary you can forward without rewriting attributions.
Whichever tool you choose, spot-check the first few summaries against the transcript. It takes two minutes and tells you how much you can trust the next hundred.
Which one should you actually pick
Choose Listently if you upload finished recordings, work in more than one language, or need audio deleted after processing. Formats covered are MP3, WAV, M4A, FLAC, OGG, MP4, MOV and MKV, with export to Word, PDF, and SRT/VTT subtitles — so it slots into both document workflows and video captioning without a conversion step.
Choose TurboScribe if you’re running very high-volume batch uploads — its Unlimited plan allows up to 50 files at once, versus Listently Pro’s 10 — and its per-file limits and interface suit your process better.
Choose Otter.ai if your audio is live English-language meetings, you want a bot that joins Zoom or Teams automatically, and recurring-speaker recognition would save you real time.
The honest summary: Otter is a meeting product, and Listently and TurboScribe are transcription products. Comparing them on a shared feature checklist obscures that.
If your files are already recorded and sitting in a folder, try Listently free — three transcriptions a day, no card required, and you’ll know within one file whether the speaker labelling holds up on your audio.
Common questions
Can I test accuracy before paying? Yes. Listently’s free plan gives you three transcriptions per day at up to 30 minutes each, which is enough to run your hardest recording — the one with crosstalk or an accent the tools usually miss — before spending anything.
What happens to my file after transcription? With Listently, uploaded audio is deleted immediately after processing, and neither audio nor transcripts are used to train AI models or shared with third parties. Other tools generally retain files until you delete them; check each policy directly.
Do I need a paid plan for long recordings? For Listently, yes — the free plan caps files at 30 minutes, and Pro removes the length limit entirely and raises uploads to 5GB. Otter’s per-conversation limits also scale with the tier you’re on.
Can I fix errors after transcription? Both the transcript text and speaker names are editable in Listently after processing finishes, and renaming a speaker updates the AI summary too, so you don’t have to correct the same name twice.