Speech-to-text model pricing compared

Per-hour cost of every transcription model BibiGPT can run, plus a few reference APIs. Token-billed models are converted with the densities we measured.

Prices checked 2026-10-26. These are upstream list prices, not BibiGPT pricing.

Modelper hour10 hList priceStrengthsIn BibiGPT
Bibi Local on-device transcription
Bibi Local desktop appSenseVoice / Whisper (on device)

Audio never leaves your machine. Speed depends on your computer.

$0$0Free (runs on your computer)
zh/en/ja/ko/yue and more
Word timestamps
On device
Desktop app, local mode
Download Bibi Local
Qwen-Audio-3.1 ASRCheapest
Alibaba Qwenqwen-audio-3.1-asr-flash-filetrans

About ¥0.075–0.10 per hour on our Chinese samples, the cheapest cloud option we measured. Better on product names than Paraformer; filler words are kept.

$0.0136Measured$0.136¥0.8 input / ¥2.7 output per 1M tokens (Beijing region)
30 languages + 10 Chinese dialects
Word timestampsSpeaker labelsHotwordsDialects
In BibiGPT
StepAudio 2.5 ASR
StepFunstepaudio-2.5-asr

The cheapest duration-billed API. Strong on Mandarin; no dialects and no speaker labels.

$0.0211$0.211¥0.15/hour ($0.022/hour)
Chinese, English
Word timestampsHotwords
In BibiGPT
Paraformer v2
Alibaba Qwenparaformer-v2

BibiGPT’s default for Chinese video, with speaker labels and filler-word removal on. Weak on brand names.

$0.0406$0.406¥0.00008/second
zh/en/ja/ko/de/fr/ru + ~18 accents
Word timestampsSpeaker labelsHotwordsFiller removalDialects
In BibiGPT
DeepSeekPOST /v1/tools/asr

Measured 1.9% CER on FLEURS Chinese (2nd of 6) and 6.4% WER on English, about 1 s per clip. Max 120 s per file and no timestamps, so it suits voice input rather than subtitles.

$0.058$0.58$0.116/hour (limited-time 50% off: $0.058), billed per second
21 languages incl. Cantonese, auto-detected
Dialects
Not in BibiGPT
Grok Voice Transcribe 2.0
xAIgrok-voice-transcribe-2.0

A cheap pick for English and other non-CJK audio. Not for Chinese.

$0.1$1$0.10/hour (batch)
25 languages (no CJK)
Word timestampsSpeaker labels
In BibiGPT
Whisper large-v3 (Groq)
OpenAI open source / Groqwhisper-large-v3

Most languages and very fast. No speaker labels; can hallucinate on silence.

$0.111$1.11$0.111/hour
99 languages
Word timestamps
In BibiGPT
Qwen3-ASR Flash
Alibaba Qwenqwen3-asr-flash-filetrans

Returns emotion labels, which 3.1 does not. No speaker labels.

$0.112$1.12¥0.00022/second
~27 languages + 4 dialects
Word timestampsEmotionDialects
In BibiGPT
Qwen-Audio-3.0 ASR
Alibaba Qwenqwen-audio-3.0-asr-flash-filetrans

Wider dialect list than 3.1, at roughly 8–10× the price.

$0.112$1.12¥0.00022/second
Widest Chinese dialect coverage
Word timestampsDialects
In BibiGPT
ElevenLabs Scribe v2
ElevenLabsscribe_v2

Reliable across languages with speaker labels. Bring your own ElevenLabs key.

$0.22$2.2$0.22/hour (batch)
90+ languages
Word timestampsSpeaker labelsSound eventsHotwords
In BibiGPT · your key
Deepgram Nova-3
Deepgramdeepgram/nova-3

A long-standing pick for English calls and meetings. Selectable with an OpenRouter key.

$0.258$2.58$0.0043/minute (OpenRouter)
Multilingual, strongest in English
Word timestampsSpeaker labelsHotwords
In BibiGPT · your key
GPT Transcribe
OpenAIopenai/gpt-transcribe

Selectable with an OpenRouter key. Text only, no timestamps or speakers.

$0.27$2.7$0.0045/minute (OpenRouter)
Multilingual
In BibiGPT · your key
Gemini 3.5 Transcribe
Googlegemini-3.5-transcribe

Removes fillers and self-corrections natively. Bring your own Gemini key.

$0.31Est.$3.1$2 audio input / $12 text output per 1M tokens (official estimate about $0.005/minute)
85+ languages
Word timestampsSpeaker labelsFiller removal
In BibiGPT · your key
Doubao recorded-audio ASR
ByteDance Volcenginevolc.bigasr.auc

Strong on Chinese and dialects. Needs a Volcengine AppID and token.

$0.324$3.24Standard ¥2.3/hour; off-peak ¥1.2; file ASR 2.0 ¥0.8
zh/en + 5 dialects
Word timestampsSpeaker labelsHotwordsDialects
In BibiGPT · your key
MAI-Transcribe 1.5
Microsoftmicrosoft/mai-transcribe-1.5

Selectable in the transcriber with an OpenRouter key.

$0.36$3.6$0.36/hour (OpenRouter)
Multilingual
Word timestamps
In BibiGPT · your key
Fish Audio Transcribe Pro
Fish Audiotranscribe-1-pro

Speaker and sound-event tags; BibiGPT strips events like [click] from subtitles. Average on Chinese names.

$0.36$3.6$0.0001/second
83 languages (vendor claim)
Word timestampsSpeaker labelsSound events
In BibiGPT · your key
StepAudio 3 ASR
StepFunstepaudio-3-asr-max

Tied first on Artificial Analysis batch WER. Without hotwords it heard “BibiGPT” as “Bilibili GPT”.

$0.394$3.94¥2.8/hour (international site $0.40/hour)
Chinese, English
Word timestampsHotwords
In BibiGPT · your key
How we convert
  • Gemini audio input: 25 tokens per second; transcript output about 3 tokens per second.
  • Qwen-Audio-3.1: about 20 input + 4 output tokens per second, measured on our own Chinese samples.
  • CNY ↔ USD at 7.1.

FAQ

Which transcription model is cheapest?

On our samples Qwen-Audio-3.1 file transcription came to about ¥0.075–0.10 per hour, below StepAudio 2.5 (¥0.15/h) and Paraformer v2 (¥0.288/h). On-device models in the Bibi Local desktop app cost nothing.

What is the difference between STT, live and TTS?

STT turns a finished recording into text and is billed per audio hour. Live models do the same while you speak, or answer you in voice, and cost more. TTS goes the other way: text in, speech out, usually billed per character.

Why are some prices marked “Est.”?

Those models bill by tokens, not minutes. We convert with the token densities listed under the table; your real bill moves with speech speed and language.

Can I use these models in BibiGPT?

Models marked “In BibiGPT” are covered by membership. “Your key” models are selectable once you paste your own API key. “On device” models run free in the Bibi Local desktop app. “Not in BibiGPT” rows are listed for reference.

Try them on your own audio

Paste a YouTube, Bilibili or podcast link into BibiGPT and pick the engine in the transcription settings. For private recordings, Bibi Local transcribes on your own computer.