Meeting notes tools fall into three categories
| Category | Examples | Role |
|---|---|---|
| Meeting bot | Otter, Fireflies | Join Zoom / Meet / Teams, transcribe live, build a team meeting library |
| Research / post-meeting organization | NotebookLM | Treat recordings as sources, then clean up transcripts, summaries, and citations afterward |
| API transcription | OpenAI Speech-to-Text, open-source Whisper | Developers package their own flow; can self-host and integrate into products |
Picking the wrong route wastes more time than picking the wrong tool, so sort this out before you compare tools.
Otter.ai: English meetings and individual / team transcripts
| Item | Details |
|---|---|
| Free | 300 monthly transcription minutes + 3 lifetime audio/video imports |
| Pro | $16.99/user/month |
| Business | $30/user/month (unlimited audio/video imports) |
| Strengths | English live transcription, speaker diarization, meeting search |
| Weaknesses | Chinese support is not as strong as Chinese-first tools |
Best for: English-first online meetings, sales / support teams with heavy online communication.
Fireflies.ai: team meeting library and collaboration
| Item | Details |
|---|---|
| Free | unlimited transcription, 800 mins storage / seat |
| Pro | $10/seat/month (annual billing, 8,000 mins storage, 20 AI credits) |
| Business | $19/seat/month (annual billing, unlimited storage, 30 AI credits) |
| Strengths | Cross-meeting search, CRM integrations, team meeting knowledge base |
| Weaknesses | A bit overkill for solo use |
Best for: sales / support / consulting teams with multiple online meetings every week.
NotebookLM: organize the material after recording
| Item | Details |
|---|---|
| Standard | 100 notebooks, 50 sources / notebook, 50 chats/day, 3 audio generations/day |
| Pro | 500 notebooks, 300 sources / notebook, 500 chats/day, 20 audio/day |
| Source limits | 200 MB or 500,000 words per file; poor audio quality may fail to import |
| Strengths | Stable Chinese transcripts, strong citations, multiple Audio Overview formats (Deep Dive / Brief / Critique / Debate), 80+ languages |
| Weaknesses | Not a live bot; you upload after the meeting |
Best for: individuals / Chinese-first workflows / tight budgets / anyone who needs transcripts + summaries + paragraph-level citations.
Whisper / OpenAI: build your own developer workflow
| Form | Details |
|---|---|
| OpenAI Speech-to-Text API | whisper-1, gpt-4o-mini-transcribe, gpt-4o-transcribe, gpt-4o-transcribe-diarize |
| Upload limit | 25 MB, with limited supported formats |
| Pricing (per minute) | Whisper $0.006, gpt-4o-mini-transcribe around $0.003, gpt-4o-transcribe around $0.006 |
| Open-source Whisper | Self-hosted, local, audio never leaves your machine |
| Strengths | Multilingual, customizable, self-hostable |
| Weaknesses | No ready-made SaaS UI, so you need to package the workflow yourself; hallucinations / typos still need human review |
Best for: developers, custom workflows, sensitive content that needs self-hosting.
Be conservative with Chinese, Taiwanese Hokkien, and mixed Chinese-English
Chinese recognition accuracy varies widely across tools because accents, recording quality, and domain-term density all matter. My suggested method:
- Find a representative recording from your normal meetings (5-10 minutes).
- Run the same clip through three tools.
- Decide based on the actual output in your own scenario.
Do not trust cross-product claims like “90% accuracy.” Those numbers come from each vendor’s own test set, and the gap between that and your real meetings is usually huge.
For Taiwanese Hokkien scenarios, the most practical route right now is Jianying / CapCut subtitles, with human proofreading afterward.
Pick a tool at a glance
| Your situation | Recommendation |
|---|---|
| Individual, Chinese-first, budget 0 | iPhone + NotebookLM |
| Individual, video / subtitles | iPhone + NotebookLM + Jianying / CapCut |
| English team, many online meetings | Otter |
| Cross-team meeting library, CRM integration | Fireflies |
| Sensitive content, must stay local | Open-source Whisper |
| Developer needs customization | OpenAI Speech-to-Text API |
Further Reading
FAQ
Q: Which AI meeting notes tool should I use in 2026?
It depends on language and workflow. Chinese-first → NotebookLM for free post-meeting organization. English / team workflows → Otter or Fireflies. Sensitive content → local open-source Whisper or the OpenAI API. No single tool covers every scenario well.
Q: What is the main difference between Otter.ai and Fireflies.ai?
Otter is stronger at English live transcription, speaker diarization, and meeting search. Fireflies is stronger as a team meeting library, with cross-meeting search and CRM integrations (800 mins of storage on the free plan). Individual / English → Otter. Team / cross-meeting library → Fireflies.
Q: Is Whisper really free?
OpenAI’s open-source Whisper itself is free, but if you run it locally, you pay for hardware and electricity. The OpenAI Speech-to-Text API uses usage-based pricing, such as Whisper at $0.006/min. A truly zero-cost route only applies when you run the open-source version locally.
Q: Which tool has the best Chinese recognition?
Chinese results vary a lot depending on recording quality, accent, and domain-term density, so cross-tool comparisons rarely produce a universal answer. My practical advice: run the same test recording through each tool first, check the result in your own scenario, then decide.
Q: Are there any tools that support Taiwanese Hokkien?
There is no perfect option yet. Jianying / CapCut Taiwanese Hokkien subtitles are usable in practice, but still need human correction. Whisper also has some Taiwanese Hokkien capability, though results fluctuate. Mixed Mandarin + Taiwanese Hokkien works better than pure Taiwanese Hokkien, and this area is still maturing.
Q: What happens after I use up the free quota?
Otter Free gives 300 minutes per month and 3 lifetime imports. Fireflies Free has unlimited transcription but 800 mins of storage. NotebookLM Standard has 50 chats / 3 audio generations per day. When you hit the quota wall, either upgrade to a paid tier or switch to a different tool.
Q: Do these tools store my recordings? Are they private and secure?
Cloud tools upload recordings to third-party servers for processing, subject to each provider’s privacy policy. If the recording must never leave your machine, run open-source Whisper locally. For a middle ground between privacy and cloud convenience, choose tools with friendly retention / no-training policies and follow your company’s security rules.
— Penchan