Rev AI human transcription $1.99 a minute vs Sume STT $0.01 a minute

Rev AI lists human transcription at $1.99 a minute, which is 199 times Sume's $0.01 a minute for machine speech-to-text. A 60-minute file costs $119.40 through Rev's human service and $0.60 through Sume STT. The price difference is what you pay for a person to check the text; the page does not say how accurate either is, and I do not claim a benchmark.

Rev's number is from its pricing page, read 2026-10-03.

Cost per file length

All figures are the per-minute price times duration.

When machine output is enough

Captions that a person skims, search indexes, clip selection and first drafts of notes usually do not need a human pass. Quotes for publication, legal records or captions for accessibility compliance may. That is your risk decision, not something this comparison settles.

A middle path is to run Sume STT first and send only the passages that matter to a human. At $1.99 a minute, a 2-minute quotation costs $3.98.

A weekly podcast

A 40-minute weekly episode costs $79.60 through Rev human transcription and $0.40 through Sume STT, so a four-episode month is $318.40 against $1.60. A hybrid sends only the 5 minutes that will be quoted to a human: $9.95 plus $0.40 for the machine pass, $10.35 an episode. I have no accuracy numbers for either side, so the hybrid is a cost sketch and not a quality claim.

What Sume does and does not do

Sume STT returns word timings with the transcript and optional sentence segments, from a public HTTPS audio URL, up to 600 seconds per job. It has no human review tier, no correction workflow and no accuracy guarantee in the docs I read. See the API reference.

Sume text to speech is $0.0475 per 1,000 characters, each quote rounded up to whole cents, up to 20,000 characters or 1,200 seconds of audio per request. Speech to text is $0.01 per minute of audio, up to 600 seconds per job.

• Use machine STT for volume and speed.
• Use a human service where the text itself is the deliverable.
• Cut a quote with the timings and render it as a caption video in the same API.