Transcribe with Whisper Large V3
4.2%
WER
99
Languages
8.0x
Speed
MIT
License
About Whisper Large V3
Model Info
- ProviderOpenAI
- Architecture-
- LicenseMIT
- UpdatedMar 2026
Zvimwe zvinobvunzwa kakawanda
Whisper Large V3 imhando yemutauro-ku-mutauro yakagadzirwa ne OpenAI. STT.ai inochengeta Whisper Large V3 pane yedu GPU infrastructure kuitira kuti iwe ugone kuishandisa pasina kuisa yako hardware. Upload audio kana video uye sarudza Whisper Large V3 kubva kumodeli picker.
Real-world kunyatsonzwisisa kunoenderana nemhando yezwi, accent, uye rurimi; For noisy kana accented rekodhi, kutarisira zvishoma zvidimbu zviviri zvemazana yepamusoro WER.
Whisper Large V3 inofamba pa STT.ai yemahara tier - chero muenzi anowana 600 maminitsi / mwedzi pasina mutengo. Yakabhadharwa mishandirapamwe inowedzera zvishoma zvishoma zvishoma, zvemukati zvemukati, uye priority queueing.
Whisper Large V3 inoburitswa pasi peMIT, iyo yakavhurika-chigadzirwa chigadzirwa chitupa. Iwe unogona kuisa Whisper Large V3 pane yako hardware kana kushandisa yedu inochengetwa vhezheni. Imwe neimwe inoshandiswa mukutengesa.
Whisper Large V3 inotsigira 99 mazita ezvinyorwa. Kuwana otomatiki kunosarudza zvirinani zita rezvinyorwa zvemavhidhiyo; unogonawo kuisarudza nemunhu kuti uwane kunyatsoita kwakanaka.
Whisper Large V3 inogadzirisa audio pazvinosvika 8.0x real-time pane edu GPUs. 1-hour audio file inosvika pasi pe 7 maminitsi; zvinopfuura zvinyorwa zvinomirira uye zvinozivisa neemail kana zvaitwa.
Whisper Large V3 ine 1.55B parameters. Larger models tend to be more accurate but slower; STT.ai hosts Whisper Large V3 on GPU so the parameter count doesn't affect your client-side performance.
Whisper Large V3 inogamuchira ese mafomati STT.ai anotsigira - MP3, WAV, M4A, FLAC, OGG, MP4, MKV, MOV, WebM, AVI, uye vamwe.Kuburitsa se TXT, SRT, VTT, DOCX, JSON, kana PDF.
Yega. Mutauro diarization inofamba pamwe Whisper Large V3 yese transcription — mumwe mutauro iri rakanyorwa uye unogona kuchinja zita ravo mu editor mushure.
Yeah. Whisper Large V3 runs in our managed environment — audio is processed and deleted by default and never used for training without explicit opt-in. Pro plans add client-side encryption for transcripts at rest.
Usati washandisa Whisper Large V3, shandisawo Whisper Large V3 vs Whisper Large V3 kuongorora kuti uone kuti Whisper Large V3 inoenderana nemhando ipi neipi yefoni. Unogona kuona WER, segment count, speaker labels, uye confidence scores side-by-side. Whisper Large V3 vs Whisper Large V3 kuongorora ndiyo inonyanya kushandiswa.
Yeah. Chidza "whisper-large-v3" separameter yemufananidzo pa /v1/transcribe endpoint. Python uye Node.js SDKs dzinosanganisira Whisper Large V3 mifananidzo. Yemahara API tier inosanganisira 100 maminitsi / mwedzi.
Yeah. Nekudaro, nekuti Whisper Large V3 ine MIT-lisensi, unogona kuichengeta iwe pachako. STT.ai's open-source peji rinonyora repo uye zviyero zveprojekiti. Zvikwata zvakawanda zvekugadzira zvinoshandisa yedu inochengetwa vhezheni kuti urege kubhadharisa GPU, kuchinja mamodheru, uye ops.