News and journalism
How accurate is Apple's new transcription AI? We tested it against Whisper and Parakeet
Marcus Mendes, 9to5Mac, 2025
Read the originalRead on October 16, 2026
- What it is
- A 9to5Mac test published on 3 July 2025. The author ran one 7-minute-31-second podcast episode through Whisper Large V3 Turbo, NVIDIA's Parakeet v2 and Apple's speech API on an M2 Pro MacBook Pro, then scored each transcript for word error rate.
- How much weight it carries
- A single test on one recording by one author, using one error-rate method, and the author says his results might vary for others. It is useful as a direction, not as a measure of Apple Dictation as it is today: the test is from 2025 and the Apple engine has changed since.
Facts taken from this source
- In a 2025 9to5Mac test of one 7-minute-31-second episode, Apple's speech API had a word error rate of 10.3 percent, against 1.5 percent for Whisper Large V3 Turbo.
“Whisper Large V3 Turbo 40 seconds 0.2% 1.5% Apple 9 seconds 1.9% 10.3%” (Results table, 'How they did')
- The 9to5Mac author who ran the 2025 test wrote that Apple's new transcription API is faster than Whisper, before testing how accurate it was.
“the fact that Apple’s new transcription API is faster than Whisper is great news” (Introduction)
- In the 2025 9to5Mac test of one 7-minute-31-second episode, Apple's speech API took 9 seconds to transcribe the audio.
“Parakeet v2 2 seconds 5.8% 12.3% Whisper Large V3 Turbo 40 seconds 0.2% 1.5% Apple 9 seconds 1.9% 10.3%” (Results table)
- The author of the 2025 9to5Mac test says the models were all evaluated the same way, but that the exact numbers would differ under slightly different methods.
“even if the exact numbers would differ under slightly different methods” (Methodology section)
- In the same 2025 9to5Mac test of one 7-minute-31-second episode, NVIDIA's Parakeet v2 had a word error rate of 12.3 percent, higher than Apple's 10.3 percent.
“Parakeet v2 2 seconds 5.8% 12.3% Whisper Large V3 Turbo 40 seconds 0.2% 1.5% Apple 9 seconds 1.9% 10.3%” (Results table, 'How they did')
- The 9to5Mac author reached Apple's speech API for the 2025 test through Finn Vorhees' open-source command-line tool, also named Yap but unrelated to this site's dictation app, on an M2 Pro MacBook Pro with 16GB of RAM.
“For Apple’s speech API, I used Finn Vorhees’ excellent Yap project. I ran them on my M2 Pro MacBook Pro with 16GB of RAM.” (How I did it)
- In the 2025 9to5Mac test of one 7-minute-31-second episode, Whisper Large V3 Turbo took 40 seconds to transcribe the audio, the longest of the three engines.
“Parakeet v2 2 seconds 5.8% 12.3% Whisper Large V3 Turbo 40 seconds 0.2% 1.5% Apple 9 seconds 1.9% 10.3%” (Results table)
- In the same 2025 9to5Mac test, Whisper Large V3 Turbo had a word error rate of 1.5 percent on the episode, the lowest of the three engines the author tested.
“Whisper Large V3 Turbo 40 seconds 0.2% 1.5% Apple 9 seconds 1.9% 10.3%” (Results table, 'How they did')
- In a 2025 9to5Mac test of one 7-minute-31-second episode, the Parakeet v2 speech model had a word error rate of 12.3 percent, the highest of the three engines the author tested.
“Parakeet v2 2 seconds 5.8% 12.3% Whisper Large V3 Turbo 40 seconds 0.2% 1.5% Apple 9 seconds 1.9% 10.3%” (Results table)
Pages that rest on this source
- Dictation and Voice to Text on iPhone and AndroidTopic
- Speech Recognition: What It Is and How Well It WorksTopic
- Transcription: How to Turn Audio and Video Into TextTopic
- Speech to Text AI: Dictation, Assistants and Voice AgentsTopic
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