Deepgram vs Cartesia

Deepgram logo

Deepgram

FreemiumAI audiospeech to text

Deepgram is a developer speech platform best known for fast, cheap, accurate speech-to-text via its Nova model family, plus Aura text-to-speech and a voice-agent API. Pricing is pay-as-you-go per minute (Nova STT from roughly $0.0077/min, with promotional rates lower) and $200 in free credits to start, making it one of the cheapest production STT options. It's optimized for real-time, high-throughput voice applications and competes directly with AssemblyAI. Like AssemblyAI, it's infrastructure for builders, not a consumer-facing tool.

Freemium · see pricing page
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VS
EDITORIAL PICK
Cartesia logo

Cartesia

FreemiumAI audiotext to speech

Cartesia builds real-time-first voice models -- its Sonic TTS and Ink STT rank #1 on Artificial Analysis speech leaderboards for combined quality and speed. Built on state-space (Mamba-style) architectures for ultra-low latency, it's purpose-made for voice agents and powers platforms like Retell. One developer API covers TTS, STT, and voice agents, with a genuinely usable free tier (20K credits/mo) and paid plans from $5/mo, plus cloud, on-prem, and on-device deployment. The main friction is an abstract credit model and promo pricing that muddies the long-term cost.

Freemium · ~27 TTS min, no commercial use). Pro $5/mo (~133 min, commercial + instant voice cloning). Startup $49/mo, Scale $299/mo, Enterprise custom. Voice agents ~$0.06/min + telephony. One API for TTS/STT/agents. As of June 2026.
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● EDITORIAL VERDICT · BIGBANGINDEX

Cartesia edges Deepgram on aggregate — 88 vs 86.

The latency king for real-time voice agents -- best-in-class speed and quality with a fair free tier, if you can stomach credit-based math. Deepgram still wins for buyers who prioritise very fast, low-latency speech-to-text. Both tools are independently scored — the right pick depends on which dimensions matter most for your workflow.

● SPEC SHEET

Side-by-side, every cell sourced.

Pricing pulled from each tool's public site. Scores follow the BigBang Score rubric — pricing transparency, free tier, API support, update frequency, unique factor, documentation, and community.

Feature
Deepgram
VS
Cartesia
Pricing model
Tier and access type
Freemium
vs
Freemium
Pricing detail
First-tier sticker
$200 free credits to start. Nova speech-to-text pay-as-you-go from ~$0.0077/min (promotional rates lower); Aura TTS and Voice Agent API priced separately. Volume and enterprise discounts. As of June 2026.
vs
Free $0/mo (20K credits
Capabilities & access
Pricing transparency
How clear the pricing page is
16/20
vs
14/20
Free tier
Free plan generosity
12/15
vs
12/15
API support
Public API + SDK quality
15/15
vs
15/15
Update frequency
Shipping cadence
14/15
vs
15/15
Quality signals
Unique factor
Differentiation from peers
12/15
vs
15/15
Documentation
Docs depth + clarity
9/10
vs
9/10
Community
Active user community
8/10
vs
8/10
Verdict
BigBang Score
Composite of all 7 signals
86/100
vs
88/100
● WHICH ONE FOR YOU?

Use-case picks.

Cut through the spec sheet. Here's what we'd recommend depending on what matters most.

Pick Deepgram if…

You prioritise very fast, low-latency speech-to-text and among the cheapest per-minute stt pricing.

DPick: Deepgram

Pick Cartesia if…

You prioritise true free tier with a commercial upgrade path and #1-ranked real-time speech quality and speed.

CPick: Cartesia

Editorial pick

Cartesia wins our composite score (88/100). It edges ahead on aggregate — but the right tool depends on which dimensions matter most.

CPick: Cartesia
BigBangIndex Editorial
Independent AI tool reviews · Updated regularly

Each comparison uses the same 7-signal BigBang Score rubric. Pricing pulled from tool sites; capabilities verified against documentation. Affiliate links are disclosed inline and never affect rank.

● FAQ

Deepgram vs Cartesia - frequently asked.

Direct answers tuned for AI search engines (ChatGPT, Perplexity, Claude) and Google's People Also Ask.

The short answer.

Cartesia wins on aggregate, but Deepgram pulls ahead on specific axes - the spec sheet above shows where each one earns its keep.