关于 语音转文本 模型
在 Modellix 探索 6 个生产可用的语音转文本 AI 模型，对比模型能力、在线试用，并通过统一 API 快速完成集成。
全部 语音转文本 模型
google/gemini-3.5-transcribe
[Core Function] Gemini 3.5 Transcribe is Google's speech-to-text model for complete pre-recorded audio. [Strengths] Accurate multilingual recognition across 85+ languages with optional language hints, custom vocabulary for brand names, speaker labels (up to 8 speakers), word-level timestamps, and Smart formatting that cleans punctuation and numbers. [Best For] Meeting notes, captions and subtitles, multilingual recordings, call logs, and speaker-attributed transcripts. [Limitations] Do NOT use this if the audio is not a public HTTPS URL, longer than 15 minutes, or larger than 300 MB. Do NOT use file upload. Do NOT combine mode=smart with word timestamps or speaker labels. This endpoint does not support live or streaming transcription. [Routing] Choose this model for Google Gemini file transcription with speaker labels or Smart formatting. For Microsoft recognition use MAI-Transcribe; for OpenAI formats such as SRT or VTT use Whisper.
xai/grok-voice-asr
[Core Function] Grok Voice ASR transcribes a single public audio URL into text via an async task. [Strengths] Word-level timestamps, optional speaker diarization, multichannel transcription, Inverse Text Normalization (format + language), keyterm biasing, and filler-word control. [Best For] Meeting notes, call-center recordings, captions, and batch audio-to-text pipelines. [Limitations] Do NOT use file upload; URL-only input. Do NOT use for live or real-time streaming transcription. Audio must be publicly reachable (max 500 MB). [Routing] Use this model for xAI Grok Voice ASR quality with URL-based audio.
openai/whisper-1
[Core Function] OpenAI Whisper transcribes a single public audio URL into text via an async task. [Strengths] Multiple output formats (verbose_json with word/segment timestamps, plain text, SRT, VTT), optional language and prompt biasing. [Best For] Meeting notes, podcasts, captions, and batch audio-to-text. [Limitations] Do NOT use file upload; URL-only input (audio up to 25 MB). Prefer verbose_json when you need duration or timestamps. [Routing] Use whisper-1 for OpenAI Whisper quality with URL-based audio.
microsoft/mai-transcribe-1.5
[Core Function] MAI-Transcribe 1.5 transcribes a single public audio URL into text via an async task. [Strengths] Multi-lingual recognition, optional locale forcing, phrase-list biasing, and word-level timestamps. [Best For] Meeting notes, captions, and batch audio-to-text. [Limitations] Do NOT use file upload; URL-only input. Do NOT expect speaker diarization. Supported audio: WAV, MP3, or FLAC up to 300 MB. [Routing] Use this model for Microsoft MAI speech recognition quality with URL-based audio.
alibaba/fun-asr-mtl
[Core Function] Fun-ASR MTL is the multi-language variant for async recorded speech recognition. [Strengths] Same parameters as fun-asr with multi-language tuning. [Best For] Mixed-language or international audio archives. [Limitations] Do NOT send more than one file per request. [Routing] Choose fun-asr for general use; fun-asr-mtl when the source audio is explicitly multi-language.
alibaba/fun-asr
[Core Function] Fun-ASR transcribes a single public audio file asynchronously. [Strengths] Hot-word vocabulary, optional speaker diarization, channel selection, and language hints. [Best For] Batch transcription of recordings up to 12 hours. [Limitations] Do NOT send more than one file per request. [Routing] Use fun-asr-mtl when multi-language optimization is preferred.
