24 field interviews of 25 minutes: 10 hours transcribed

Transcribing 24 field interviews of 25 minutes each is 600 audio minutes, or 10 hours, which costs $5.40 on MAI-Transcribe-2-Streaming and $6.00 on Sume STT 1.0 in 72 jobs.

Field audio is often noisy or mixed-language, so test a sample before the whole set.

The arithmetic

MAI-Transcribe-2-Streaming is priced per hour, Sume STT 1.0 per audio minute, so the sums convert minutes to hours first. The Sume rate is the public rate on the Sume docs; confirm the live number in GET /v1/catalog.

Per minute, MAI works out to $0.009 ($0.54 / 60) against Sume's $0.01, so Sume is about 11 percent higher. On this run the difference is $0.60. Microsoft's rate is an introductory price that its page says runs through the end of the year, and the page does not say what the price becomes afterward, so a budget past December should not assume it.

A sample first

Run 3 interviews first, about 75 minutes and 75 cents on Sume, and read them against the recording. If names and places are wrong, decide on a proofreading budget before you run the other 21.

Neither price tells you how an option handles your noise level, so test your own recordings.

• Pass language_code when the interview is in one known language.
• Keep the first sample's job ids as the baseline.

Limits that shape a Sume run

Sume does not list MAI-Transcribe-2-Streaming, so the MAI row is a price reference. Sume STT 1.0 takes a public HTTPS audio_url and returns the transcript with word timings; there is no flag for timings because they always come back. Sentence segments are available when you send segmentation.

• duration_seconds is an optional hint from 1 to 600; leave it out and Sume reserves one minute, so send it for a long file.
• language_code is a hint such as en or ko; leave it out for auto-detect.
• diarize and tag_audio_events are fixed server-side, so do not send them; there are no speaker-label controls.
• The MAI price is an introductory rate that Microsoft says runs through the end of the year.

Running it

Submit with stt_create and an idempotency_key, wait with jobs_wait, then read jobs_result for the text and words. Cut recordings longer than 10 minutes at a pause first; audio detach pulls the track out of a video and Timeline audio split slices a Sume-hosted file into ranges.

The figures are list arithmetic as of 2026-10-08. A one-time check of your own audio is worth more than a benchmark, so run one representative file through each option before you commit a budget.