Audio Transcriber — Deepgram Nova-3 Speech-to-Text avatar

Audio Transcriber — Deepgram Nova-3 Speech-to-Text

Pricing

from $10.00 / 1,000 audio minute (zero setup)s

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Audio Transcriber — Deepgram Nova-3 Speech-to-Text

Audio Transcriber — Deepgram Nova-3 Speech-to-Text

Transcribe audio and video file URLs with Deepgram Nova-3. Zero setup at $0.01/min — or bring your own Deepgram key and pay $0.004/min. Speaker diarization, SRT subtitles, summaries, language detection.

Pricing

from $10.00 / 1,000 audio minute (zero setup)s

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Developer

Heim AI

Heim AI

Maintained by Community

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8

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2 days ago

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Transcribe any audio or video file URL with Deepgram Nova-3. Zero setup at $0.01/min — or bring your own free Deepgram key and pay just $0.004/min. Speaker diarization, SRT subtitles, summaries, word timestamps, and automatic language detection. Runs out of the box: press Start and the sample file transcribes.

Why this one

  • Cheapest way to run Deepgram on Apify. Zero-setup mode is $0.01 per audio minute, all-in ($0.60/hour). With your own Deepgram key (free, $200 starting credit, no card) the actor fee drops to $0.004/min — you pay Deepgram's wholesale ~$0.0043/min directly, about $0.50/hour total.
  • Nova-3, not a black box. You choose the model (nova-3, nova-2, whisper-large), the language, and exactly which extras to compute. No hidden engine, no quality lottery.
  • Built for pipelines and agents. Feed it a list of URLs, get one clean JSON row per file. Chain it after any scraper that outputs media links, schedule it, or call it from your agent via MCP.
  • HTTP-only and light. Deepgram fetches your URL directly — nothing is downloaded through the actor, so runs are fast and there are no proxy or compute surcharges.

What it does

Give it direct links to audio or video files (mp3, wav, m4a, flac, ogg, opus, mp4, mov, webm, mkv — up to 2 GB each). For every file you get:

FieldAlways / opt-inDescription
transcriptalwaysFull text, smart-formatted, paragraph breaks
durationSeconds, minutesBilledalwaysAudio length and what you were charged
language, confidence, modelalwaysDetected/requested language, overall confidence
summaryopt-inShort abstract summary (English)
speakerTranscriptwith diarizationSpeaker 0: ... labeled dialogue
srtopt-inReady-to-save subtitle file content
utterancesopt-inTimestamped spoken segments with speakers
wordsopt-inPer-word timing and confidence

Failed files become { "type": "error", "url", "error" } rows — one bad link never kills the batch, and you are never charged for failures. Skipped inputs (invalid URLs, duplicates, anything past the 500-file cap, or files left over after your run's charge limit) are also recorded as rows, so your input list always reconciles against the dataset. Silent or speech-free audio that decodes successfully is billed by duration like any other file — Deepgram processes the full recording either way.

Pricing

EventPriceWhen
Audio minute (zero-setup)$0.010No key provided — transcription cost included
Audio minute (your Deepgram key)$0.004deepgramApiKey set — you pay Deepgram directly at cost
Actor start$0.00005Per run

Minutes are rounded up per file. A 90-second podcast clip = 2 minutes = $0.02 (zero-setup). A 1-hour meeting = $0.60 zero-setup, or ~$0.50 all-in with your own key.

Worth knowing: the bring-your-own-key discount pays for itself fast. Deepgram gives new accounts $200 of free credit with no card — that alone covers ~775 hours of Nova-3 pre-recorded transcription before you pay Deepgram anything.

Quick start

{
"audioUrls": ["https://example.com/interview.mp3"],
"diarize": true,
"includeSrt": true
}

Podcast pipeline (schedule it): scrape episode URLs with any RSS/podcast actor, feed the enclosure URLs here, get transcripts + summaries into your dataset every morning.

Meeting archive: point it at your recording exports (any public or signed URL works), turn on diarization and utterances, index the output in your search tool.

Agent use: this actor is MCP-ready — an agent can pass a media URL and read back the transcript JSON in one call.

Input reference

  • audioUrls (required) — direct file links. Not YouTube/TikTok page URLs; use a media-downloader actor first if you need those.
  • deepgramApiKey — optional. Stored encrypted, sent only to api.deepgram.com, never logged.
  • modelnova-3 (default), nova-2, whisper-large.
  • language — BCP-47 code (en, es, zh, ...). Use multi with nova-3 for code-switched audio, or set detectLanguage and forget about it.
  • diarize, smartFormat, paragraphs, summarize, includeSrt, includeUtterances, includeWords — feature toggles, all documented in the input form.
  • keyterms — nova-3 keyterm prompting: pass product names, jargon, or speaker names to boost their recognition.

FAQ

Do I need a Deepgram account? No — zero-setup mode works immediately. Bring a key only if you want the lower rate.

What audio quality/languages are supported? Nova-3 supports 30+ languages and handles noisy, multi-speaker, real-world audio; whisper-large covers 90+ languages for rarer cases.

Is my audio stored? The actor never downloads or stores your media — Deepgram fetches the URL, returns JSON, and the actor keeps only the transcript in your dataset.

File limits? 2 GB per file, up to 500 files per run, ~10 minutes max processing per file (Deepgram's cap). Batches run 4 files at a time (2 for Whisper, which has stricter concurrency limits). Long runs are checkpointed — a platform migration resumes where it left off instead of re-billing finished files.

Why did my URL fail? It must be a direct, publicly reachable media file (or signed URL). Page URLs (YouTube, Spotify, Drive share pages) are not media files.


Found this useful? A review on the actor page helps other people find it — and tells me what to build next. Hit a problem? Open an issue and I'll fix it fast.

Telemetry

Each run records one anonymous telemetry event to the developer's own storage: a salted hash of the caller account ID (never the raw ID), the run origin (e.g. web console vs API), and a timestamp. No inputs, results, or personal data are collected - this only measures adoption (distinct and returning users).