Shotcraft
Voice and speech

OpenAI transcription (gpt-4o-transcribe, gpt-transcribe, Whisper)

A family of speech-to-text models spanning batch and realtime use: Whisper and gpt-4o-transcribe for files, gpt-4o-transcribe-diarize for speaker-separated transcripts, and gpt-live-transcribe / gpt-realtime-whisper for streaming. gpt-transcribe is the cheapest per-minute option on the pricing page.

A speech model by OpenAI · read 2026-08-14 · sourcing high

Weights
Not released
API
Yes
Commercial use
Vendor states commercial use is permitted
Commercial use — Vendor states commercial use is permitted

Note the open-weights Whisper release (MIT) is a separate artefact from the hosted whisper-1 endpoint priced here.

The licence notes recorded during research were read for a commercial-use position and did not state one. Read the licence before you rely on any of this. Nothing on this page is legal advice, and this site does not tell you a model is cleared for commercial use.

Specification

Vendor figures, read 2026-08-14Read from OpenAI's own documentation on 2026-08-14. Vendors change these between model versions without announcing it, so check theirs before you commit a shot to a number. Sourcing for this entry is strong: the figures came from pages we retrieved and read. Check the vendor's current documentation

What it takes in
audio
What it makes
text
Controls
timestamps, streaming-low-latency
Weights
Not released
API
Yes
Pricing
gpt-transcribe $0.0045/min; Whisper $0.006/min; gpt-4o-transcribe $0.006/min (or $2.50/1M input, $10.00/1M output tokens); gpt-4o-mini-transcribe $0.003/min (or $1.25/$5.00 per 1M); gpt-4o-transcribe-diarize $0.006/min; gpt-live-transcribe and gpt-realtime-whisper $0.017/min; gpt-realtime-translate $0.034/min.
Released or updated
not established
Languages
not established

Strengths

  • Cheapest verified batch transcription in this dataset at $0.0045/min
  • Diarization available as a dedicated model
  • Both batch and streaming options in one API
  • Whisper's open weights give an on-prem fallback

Weaknesses

  • Language counts and word error rates not documented on the pages fetched
  • File size and duration limits not confirmed from the pages fetched
  • Model naming is confusing and churning (five overlapping transcribe models)
  • Streaming costs ~4x batch

Best for

What to understand before using it

Explainers naming the mechanisms this model's own documentation mentions.

MCP servers that front OpenAI

Servers in the media MCP directory whose own description or homepage names this vendor. Absence of a server here is not evidence that none exists: most publish no tool list at all.

See it from the vendor

Shotcraft hosts no sample output. Judging a model means watching its own showreel with your own eyes, and a clip re-hosted here would be a clip we chose.

Nearby in the directory

gpt-4o-mini-tts

OpenAI's current text-to-speech model, steerable with natural-language instructions about how a line should be delivered. It replaces the older tts-1

Voice and speech

gpt-realtime-2.1

OpenAI's speech-to-speech model for live conversation, taking audio in and producing audio out with tool use. A mini variant trades quality for roughl

Voice and speech

Azure AI Speech text-to-speech (Neural, Neural HD, MAI voices)

Microsoft's enterprise speech synthesis service, with 200+ prebuilt neural voices across 80+ locales plus tiers for HD voices, multilingual voices, mu

Voice and speech

Sources

Read on 2026-08-14. A source that has changed since then will not be reflected here until the next pass.