whisperkit-coreml

OpenAI Whisper in CoreML format, published by Diction Labs for on-device speech-to-text on Apple hardware. Everything here is our own build, made with whisperkittools (MIT) from OpenAI's MIT-licensed Whisper checkpoints.

Use with WhisperKit

let config = WhisperKitConfig(
    model: "openai_whisper-base",
    modelRepo: "DictionLabs/whisperkit-coreml"
)
let pipe = try await WhisperKit(config)

Runs on argmax-oss-swift (MIT). Tokenizers are resolved separately from the matching openai/whisper-* repo, so a first run still needs network access even with the weights already on disk.

Variants

Folder	Base model	Size
openai_whisper-base	openai/whisper-base	full precision
openai_whisper-small	openai/whisper-small	full precision
openai_whisper-large-v3-turbo	openai/whisper-large-v3-turbo	full precision, 1.63 GB
dictionlabs_whisper-large-v3-turbo-q6q8	openai/whisper-large-v3-turbo	compressed, 703 MB

dictionlabs_whisper-large-v3-turbo-q6q8 is a compressed version of the turbo model above, same weights, reduced precision, about half the size. Verified against the full precision build with real transcription tests, not just internal accuracy checks:

Language	Full precision (WER/CER)	Compressed (WER/CER)
German	2.8%	3.4%
English	15.5%	15.5%
French	7.8%	8.8%
Japanese	2.6%	2.6%
Korean	18.1%	22.5%
Chinese	9.0%	9.0%

Licence

MIT, same as upstream Whisper.