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Deepgram vs Tunk

Two fact sheets from our own research, side by side — pricing, platforms, API access and status re-checked by us rather than quoted from the vendors.

The short answer

Free plan
Only Deepgram (Tunk has paid plans only)
Public API
Both have one
Higher Trust score
Deepgram — 94 vs 79 for Tunk
Best fit
Deepgram: Engineering teams building real-time transcription or voice agents who want published per-minute rates · Tunk: Teams evaluating speech APIs from an India-based vendor
Status
Both up at our last check (Sep 6, 2026)

From our own records as of each tool's last check. Anything we have not confirmed is left out rather than guessed. How we verify

DeepgramLow-latency speech recognition and voice agent APITunkSpeech-to-text and voice-agent APIs from an Indian vendor, with browser playgrounds for both

Side by side

FactDeepgramTunk
CategorySpeech-to-Text & TranscriptionSpeech-to-Text & Transcription
Pricing modelFreemiumPaid
Starts at$0.0043/min—
Public APIYesYes
Trust score94 / 10079 / 100
PlatformsAPIWeb, API
CompanyDeepgram, Inc.LogicNimbus Private Limited
Launched2015—
Last verifiedSep 6, 2026Sep 6, 2026

What our research says

Deepgram

Deepgram is the pick when you are building the pipeline yourself and the per-minute number matters: streaming Nova-3 at under half a cent a minute, published rates for every model and mode, and a $200 credit that does not expire make it easy to size a bill before signing anything. It is an API, not a product — there is no transcription app to hand to a non-developer, and the voice agent tier is priced per connected minute, so idle sessions cost money.

Pros

  • Rates are public down to a fraction of a cent, per model and per mode
  • $200 starting credit with no card and no expiry is enough to benchmark seriously
  • Streaming and batch share one API, and the Voice Agent API saves wiring STT, LLM and TTS together
  • Founded 2015 and Series C funded, with self-hosted deployment on enterprise terms

Cons

  • Streaming rates are marked as limited-time promotional, so the published number may rise
  • Voice Agent minutes are billed on WebSocket connection time, including silence
  • Growth pricing starts at a $4,000 annual prepay, with nothing between pay-as-you-go and that

Tunk

A small Indian voice-AI vendor covering both halves of the stack — recognition and agents — with playgrounds you can poke at before wiring anything up. What we could not establish is the thing that decides whether it is worth trying: the rate. Nothing on the site rendered a price for us, and there is little third-party coverage to check it against.

Pros

  • Covers both speech-to-text and voice agent building from one account
  • Interactive playgrounds for both products, not just API documentation
  • Names a real legal entity and registered Indian address on the site

Cons

  • Pricing page renders no figures, so the rate is unknown until you sign up
  • No published accuracy or latency benchmarks
  • Small vendor with thin third-party coverage to corroborate its claims

Which one fits

Choose Deepgram if you need

  • Engineering teams building real-time transcription or voice agents who want published per-minute rates
  • Contact-centre and meeting products with enough audio volume for the Growth discount to justify a prepaid year
  • Developers who want speech-to-text, text-to-speech and an agent runtime from one vendor and one key

Choose Tunk if you need

  • Teams evaluating speech APIs from an India-based vendor
  • Building voice agents and transcription against a single provider
  • Trying real-time recognition in a browser playground before integrating

Deepgram vs Tunk: the questions people ask

Is Deepgram cheaper than Tunk?

Deepgram starts at $0.0043/min. An entry price for Tunk is not confirmed by us yet, so check its pricing page before you compare.

Does Deepgram or Tunk have a free tier?

Deepgram has a free tier; Tunk has paid plans only.

Which has a public API, Deepgram or Tunk?

Both ship a public API, so either can be built on; the fact table above shows the platforms each one runs on.

More comparisons

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