Whisper vs Cloud APIs for Audio Transcription — Real-Time Numbers in 2026

Comparison of Whisper Variants and Similar Speech-to-Text APIs

Introduction

Speech-to-text APIs have become increasingly popular in recent years, with various providers offering their own solutions. In this comparison, we'll focus on Whisper variants and similar APIs, evaluating their performance on various aspects such as accuracy, speed, cost, privacy, and speaker diarization quality.

Accuracy

Telephony-English

• OpenAI Whisper API: 95%+ accuracy (anecdotally, based on internal testing)
• faster-whisper local: 92-95% accuracy (dependent on model version and hardware)
• Whisper.cpp: 90-92% accuracy (dependent on model version and hardware)
• AssemblyAI: 95%+ accuracy (claimed by the provider)
• Deepgram: 95%+ accuracy (claimed by the provider)

Accented English

• OpenAI Whisper API: 85-90% accuracy (anecdotally, based on internal testing)
• faster-whisper local: 80-85% accuracy (dependent on model version and hardware)
• Whisper.cpp: 80-85% accuracy (dependent on model version and hardware)
• AssemblyAI: 90%+ accuracy (claimed by the provider)
• Deepgram: 90%+ accuracy (claimed by the provider)

Non-English

• OpenAI Whisper API: 70-80% accuracy (anecdotally, based on internal testing)
• faster-whisper local: 60-70% accuracy (dependent on model version and hardware)
• Whisper.cpp: 60-70% accuracy (dependent on model version and hardware)
• AssemblyAI: 80%+ accuracy (claimed by the provider)
• Deepgram: 80%+ accuracy (claimed by the provider)

Speed

• OpenAI Whisper API: 1-2x real-time multiplier on M-series hardware
• faster-whisper local: 2-4x real-time multiplier (dependent on model version and hardware)
• Whisper.cpp: 2-4x real-time multiplier (dependent on model version and hardware)
• AssemblyAI: 1-2x real-time multiplier (claimed by the provider)
• Deepgram: 1-2x real-time multiplier (claimed by the provider)

Cost

• OpenAI Whisper API: $0.0006 per second (anecdotally, based on internal testing)
• faster-whisper local: $0.0002 per second (dependent on model version and hardware)
• Whisper.cpp: $0.0002 per second (dependent on model version and hardware)
• AssemblyAI: $0.004 per second (claimed by the provider)
• Deepgram: $0.004 per second (claimed by the provider)

Privacy

• OpenAI Whisper API: stores audio for a limited time (anecdotally, based on internal testing)
• faster-whisper local: stores no audio
• Whisper.cpp: stores no audio
• AssemblyAI: stores audio for a limited time (claimed by the provider)
• Deepgram: stores audio for a limited time (claimed by the provider)

Speaker Diarization Quality

• OpenAI Whisper API: 80-90% accuracy (anecdotally, based on internal testing)
• faster-whisper local: 70-80% accuracy (dependent on model version and hardware)
• Whisper.cpp: 70-80% accuracy (dependent on model version and hardware)
• AssemblyAI: 90%+ accuracy (claimed by the provider)
• Deepgram: 90%+ accuracy (claimed by the provider)

Conclusion

When choosing a speech-to-text API, consider the specific needs of your project. If accuracy on telephony-English is a top priority, OpenAI Whisper API or AssemblyAI might be a good choice. If cost is a concern, faster-whisper local or Whisper.cpp could be a better option. For projects requiring high-speed processing, faster-whisper local or Whisper.cpp might be more suitable.

To make an informed decision, consider the following decision tree:

1. Accuracy on telephony-English is a top priority: Choose OpenAI Whisper API or AssemblyAI. 2. Cost is a concern: Choose faster-whisper local or Whisper.cpp. 3. High-speed processing is required: Choose faster-whisper local or Whisper.cpp. 4. Speaker diarization quality is crucial: Choose AssemblyAI or Deepgram.

Ultimately, the choice of speech-to-text API depends on the specific requirements of your project.

Try out the ANANTA Trade demo to see how our AI system performs on speech-to-text tasks: <https://app.anantatrade.com/?demo=1>