AssemblyAI vs OpenAI Whisper
An independent, side-by-side comparison to help you pick the right tool. Pricing, features, strengths, and trade-offs.
Free tier / Pay-as-you-go from $0.015/min
Free (open source) / API $0.006/min
At a glance
| AssemblyAI | OpenAI Whisper | |
|---|---|---|
| Pricing | Free tier / Pay-as-you-go from $0.015/min | Free (open source) / API $0.006/min |
| Type | Transcription | Transcription |
Feature comparison
| Feature | AssemblyAI | OpenAI Whisper |
|---|---|---|
| Speech-to-text API | — | |
| LeMUR (LLM for audio) | — | |
| PII redaction | — | |
| Topic and sentiment detection | — | |
| Speaker diarization | — | |
| 99 language support | — | |
| Local processing option | — | |
| Open-source model | — | |
| OpenAI API access | — | |
| Speaker diarization (via community tools) | — |
What makes each tool different
AssemblyAI
AssemblyAI goes beyond transcription to provide audio intelligence: topic detection, sentiment analysis, entity recognition, PII redaction, and auto chapters. Its LeMUR feature lets you ask LLM-powered questions about transcribed audio.
OpenAI Whisper
Whisper changed the transcription landscape by providing a free, open-source model with near-commercial accuracy. It supports 99 languages, runs locally for privacy, and spawned an ecosystem of tools and services built on top of it.
Strengths and weaknesses
Strengths
- Rich audio intelligence features beyond transcription
- LeMUR enables Q&A on audio content
- Excellent developer documentation
Weaknesses
- Higher per-minute cost than Deepgram
- No real-time streaming (batch only)
- English-focused accuracy
Strengths
- Free and open source
- Excellent multilingual accuracy
- Can run fully offline for privacy
Weaknesses
- Raw model requires technical setup
- No built-in speaker diarization
- CPU inference is slow without GPU
Try both and decide
The best way to choose is to test each tool with your own workflow. Most offer free tiers or trials.