I run a lot of meetings and I’ve wasted money on transcription tools that did half of what I needed. The category isn’t one thing anymore. It’s three different jobs wearing the same label: meeting notes, podcast and video editing, and raw speech-to-text APIs for developers. A tool that crushes one of those is usually mediocre at the other two. Here’s how to pick the one that actually fits your workload, with the real pricing and the tradeoffs nobody puts on the landing page.
Why the AI Transcription Category Split Into Three
Five years ago “AI transcription” was one thing. Audio goes in, text comes out. That’s not the category anymore.
The tools now compete on what happens after they make the transcript. Meeting tools summarize and sync to your CRM. Podcast tools let you edit audio by cutting text. APIs hand you streaming output with speaker labels and diarization so you can build whatever you want on top.
The transcription itself is now commodity-good across the board. Your decision is workflow, not accuracy.
I’ve watched a few teams burn money here. Someone buys Otter for podcast editing and gets frustrated. Someone grabs Descript for standup notes and wonders why they’re paying for video editing they’ll never touch. These tools overlap, but they don’t really substitute for each other.
Pick the one that matches the job.
Otter.ai: Still the Best for Live Meetings
Otter’s been doing the same thing since 2018, which sounds like a criticism but isn’t. When a tool sticks around that long in one niche, it’s usually because it actually works. If you need live captions in Zoom, Google Meet, or Teams, Otter’s the one I’d point most people to first. The sidebar AI joins the meeting, can answer questions on the fly, and the search across your meeting history is genuinely good.
I poked around their setup docs and a bunch of G2 reviews while writing this. One thing that came up over and over: people love being able to search “what did we say about X” and actually get an answer. Sounds trivial until you’ve tried it on a year of meetings in a weaker tool.
Pricing runs from a free plan at 300 minutes a month up to Pro at around $16.99 a user a month, with 1,200 minutes per user on Pro. That covers most solo workloads. The honest tradeoff: Otter’s AI summaries used to lead the category, but Fireflies has caught up. If summaries matter more than search to you, keep reading.
Fireflies.ai is the pick if you’re running a revenue team. Its integrations with Salesforce, HubSpot, Outreach, and Salesloft run deeper than anything else I looked at. It handles 60-plus languages too. The free tier is actually usable, with 800 minutes a month covering most small teams. Paid plans start around $19 per user per month.
What stood out reading vendor docs and a pile of G2 reviews was the Smart Summary. It comes out clean enough to forward without a rewrite pass, which most transcription tools can’t claim. The Channels feature is unique: teams subscribe to meeting topics and get auto-summaries dropped in. Tradeoff: live captioning lags behind Otter, and search across old meetings feels half-finished.
Descript works backwards from everything else on this list. It transcribes your file, then makes the transcript your editing surface. Delete a sentence in the text and the clip cuts itself. Type a new word and it slots into the timeline. The whole flow is built around text manipulation, not timeline scrubbing. If you run a podcast or edit video, this is the only tool here that does it, and once you’ve seen it work, a traditional editor feels slower than it should.
Pricing starts at the Hobbyist tier around $24 a month, dropping to roughly $16 on annual billing. The free plan gives you about an hour a month and includes dynamic captions, screen recording, and speaker detection. The honest tradeoff: that free hour is the stingiest of any tool in this roundup, and Descript isn’t really built for meeting notes or live captioning. Buy it for the editing, not for the meetings.
Riverside: Best for Recording Remote Interviews
If you’re recording remote interviews or podcast conversations with guests, Riverside is worth a look. It records each participant locally in broadcast quality, so you get a clean file for every speaker even when someone’s internet is shaky. Standard plans run about $19 a month, with a free tier of two hours.
The killer scenario is a guest with a bad connection. Riverside keeps their local audio clean where cloud-only tools would degrade the whole recording. It also leads the pack on language support at 100-plus, which I noticed going through their docs and a few G2 threads.
But it’s not a general-purpose meeting tool. The editing features are thin compared to Descript, and you’re really paying for the recording workflow.
Pick it for that. Pair it with something else for editing.
Deepgram: The Developer-First Transcription API
Building speech-to-text into your own product? You want an API, not another SaaS dashboard. Deepgram is what most developers seem to recommend. Their Nova-2 model is built for streaming, and the latency numbers hold up in vendor docs and the community threads I’ve read. Usage-based pricing runs about $0.0043 per minute for streaming and $0.0078 for async. It scales sensibly as volume grows.
The whole pitch is speed. If you’re wiring up a voice agent or live captioning, sub-second latency is the difference between feeling responsive and feeling broken. That’s where Deepgram wins. The catch: you build everything else yourself. No meeting UI, no summaries, no CRM sync. I went through their quickstart docs and the API is straightforward, but you’re definitely the integrator here. Not a tool for non-developers.
AssemblyAI: The Feature-Rich API Alternative
AssemblyAI sits between Deepgram and the heavier enterprise APIs. You get solid transcription plus audio intelligence features on top: chapter detection, topic extraction, entity detection, and sentiment analysis. Pricing runs about $0.0066 per minute for async, with volume discounts if you push enough audio through.
I’ve spent time in their docs and read through community threads on Reddit and their Discord. The SDKs are clean and the documentation is actually usable, which counts for a lot. The catch: per-minute cost is a bit higher than Deepgram at low volume, and there’s a real learning curve if you’ve never touched audio APIs before. Manageable, but don’t expect to ship something in an afternoon.
OpenAI Whisper: The Free Self-Hosted Option
Whisper flipped the script by open-sourcing a model that holds its own against paid APIs, with zero licensing cost. That’s the headline. If you can self-host it and you don’t need real-time streaming, the price is hard to beat.
You eat the compute cost on your own hardware and that’s the entire bill. Or you skip the infra work and pay OpenAI’s hosted API. Both paths work, and the API gives you nearly the same accuracy without the maintenance burden.
The tradeoffs are real though. Whisper wants longer audio before speaker diarization gets reliable. Latency sits well above Deepgram’s. And once you self-host, you’re the one paging through logs when something breaks at 2am. It’s a smart pick for batch jobs and teams pinching pennies. It’s the wrong pick for real-time voice agents where every second of lag matters. Reading through community threads and the vendor docs, that lines up with what most people report.
Pricing at a Glance
Pricing pages are where vendors get creative with words. Skip the marketing copy. Here’s what you’ll actually pay to start, and heads up: the monthly sticker is rarely what lands on the invoice once you commit to annual billing. Most knock 20 to 50 percent off if you go yearly.
- Otter: free at 300 min/mo, Pro around $16.99 per user for 1,200 min.
- Fireflies: free at 800 min/mo, Pro around $19 per user.
- Descript: free about 1 hour/mo, Hobbyist $24/mo monthly or about $16 billed annually.
- Riverside: free at 2 hours/mo, Standard about $19/mo.
- Deepgram: usage-based, roughly $0.0043/min streaming and $0.0078/min async.
- AssemblyAI: roughly $0.0066/min async, volume discounts kick in fast.
- Whisper: open source, free license, you pay only for your own compute.
The free tiers are where people get burned. They look comparable on paper. Fireflies’ 800 minutes actually means something useful. Otter’s 300 evaporates after a couple of weekly meetings. And Descript‘s single hour is enough to test the editor workflow and not much else. Do the math on your real meeting volume before you let the free tier decide the winner for you.
Real Workflows, Not Feature Lists
Feature tables all blur together after a while. The workflow differences are where things actually separate. Three come up over and over.
The solo consultant drowning in client calls. They record every call, need a clean summary to send the client, and want a searchable archive for billing and follow-ups. Fireflies fits this well. The Smart Summary is sendable as-is, and the CRM sync drops the notes next to the client record without manual filing. $19 a month to never write a recap email again pays for itself inside a week of calls.
The podcaster shipping two episodes a week. Wants clean audio from every guest and fast turnarounds. Riverside handles the recording side and keeps each guest’s local audio at broadcast quality even on sketchy connections. Then drop the files into Descript to edit by cutting text and to add captions for clips. That two-tool combo runs around $43 a month and replaces an editor. It’s a stack I see recommended constantly in podcasting communities and indie creator threads.
Then there’s the product team building a voice agent. They need streaming transcription with low latency because the agent talks to customers in real time. That’s a Deepgram or AssemblyAI job, not an app job. Deepgram wins on raw speed. AssemblyAI wins if you also want sentiment, topics, and entities without wiring up extra models on your end.
One thing I’d flag from reading through vendor docs and G2 threads: don’t make this call based on benchmark numbers. Latency swings wildly depending on your audio quality, accents, and network path. Test on your own recordings before you commit. From what I’ve seen in deployment writeups, the gap between the marketing slide and a real production workload is usually bigger than people expect.
Common Mistakes People Make
Same mistakes keep showing up. They cost real money.
Buying a meeting tool for editing. If you’re a content creator who grabs Otter or Fireflies because they’re popular, you’ll find out fast there’s no way to clean up a transcript by editing text. You end up buying Descript anyway. I’ve watched this exact cycle play out more than once. Start with the editing tool if that’s your main job.
Judging accuracy on clean audio. Every tool scores well when the audio is studio-clean. Your real meetings have background noise, accents, and people talking over each other. Test with your own recordings before you commit. Gaps that look tiny in a demo get annoying fast in production.
Ignoring the security side. Meeting transcripts often contain sensitive internal or client info. Before you hand every call to a third-party vendor, check where the data lives and whether your team’s privacy rules allow it. Worth sorting out before you sign anything. Undoing it later is a lot more work.
Why the Old Advice No Longer Applies
Most transcription reviews are useless now. They treat Otter, Fireflies, and Descript like they’re the same product with different logos. They’re not.
Two things changed. Accuracy got good enough that “which is most accurate” doesn’t matter much anymore. At 95% vs 97%, you still need to fix names and jargon either way. The tools also split into genuinely different workflows. Otter is built around live meetings. Descript is built around editing audio by editing the text. The APIs are infrastructure you wire into something you already built.
When I went through vendor docs, G2 reviews, and a few Reddit threads for this post, the real question in 2026 isn’t which model wins on Word Error Rate. It’s which workflow you actually need. Figure that out and the tool choice mostly picks itself.
The Bottom Line
Accuracy isn’t the deciding factor anymore. Every tool here hits 95%+ on clean audio, and yours almost certainly won’t be clean audio. What actually matters is workflow fit. Pick the tool that matches how you spend your day, run it on the free tier for a week, and only pay once you know you’ll use the summaries, editor, or integrations regularly.
If you’re picking blind, my default move is Otter or Fireflies on the free plan. Most people want meeting notes, and those two handle that workflow without much fuss. Skip straight to Descript if you’re making content or editing podcasts — the meeting tools aren’t built for that. And if you’re a developer wiring transcription into a product, run Deepgram against AssemblyAI against your own audio files. The marketing benchmarks won’t match what you actually record in production.