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AI Voice & Speech Comparison

Deepgram vs. Vapi

At a glance

At a glance

Deepgram

Best for

Best for developers building real-time speech-to-text, text-to-speech and voice agents through an API.

  • Small and mid-sized
  • Enterprise

Vapi

Best for

Best for developers putting voice agents on real phone lines for support, lead qualification or scheduling.

  • Small and mid-sized
  • Enterprise

Cataleo does not name a winner. Both statements come from the vendors themselves.

Full Comparison

Criterion Deepgram Vapi
Starting price Usage-based, pay-as-you-go No minimums and no expiry. Speech-to-text from $0.0048 / minute on Nova-3 monolingual streaming, text-to-speech from $0.0150 / 1,000 characters on Aura-1, and the Voice Agent API from $0.056 / minute. From $0.05 / minute of calls Build plan, usage-based, plus $0.005 per SMS or chat message. Ten concurrent lines are included and further lines cost $10 / month each. Model provider costs for speech-to-text, the LLM and text-to-speech are passed through at cost, or nothing if you bring your own API keys.
Free trial $200 in free credits to start, no credit card required Not stated
Commercial use Yes, usage-based Yes, usage-based
Output Speech-to-text, text-to-speech and voice agents Voice agents for inbound and outbound phone calls, web voice, and SMS or chat
API Yes Yes, REST API, CLI and SDKs
Hosting Cloud, or self-hosted for in-region and in-house data control Not stated
Voice cloning No, the catalogue is fixed: 40+ prebuilt Aura-2 voices across English, Spanish, Dutch, French, German, Italian and Japanese, with no cloning or custom-voice product on the price list Not part of Vapi itself; voices come from connected providers such as ElevenLabs and Deepgram
Real-time use Yes, real-time streaming speech-to-text and text-to-speech, plus batch processing Yes, live inbound and outbound phone and web conversations at an average latency under 500 ms
Languages 45+ languages for speech-to-text, with automatic language detection Depends on the providers chosen for a given assistant: automatic language detection and code-switching with Deepgram (100+ languages), Google STT (125+) or Gladia (110+), while Azure, OpenAI Whisper, Speechmatics and Talkscriber run one language at a time; on the voice side Vapi's own voices cover 40+ languages, Azure 140+ and ElevenLabs 30+. The languages an assistant may use have to be listed in its system prompt
Speech-to-speech and dubbing No dubbing or translation product. Speech-to-speech runs as a pipeline through the Voice Agent API, which handles listening, thinking and speaking with configurable speech-to-text models, LLM providers and voices, plus function calling mid-conversation Yes, a call runs as spoken conversation by chaining speech-to-text, a language model and text-to-speech, with natural turn-taking
Editing and controls Voice selection, plus encoding, bit rate, container and sample rate on the output, streamed audio and callbacks. Aura-2 is built to read naturally without SSML markup, and speed and style can be changed mid-conversation without restarting the session Assistants for a single prompt with tools, Squads for multi-assistant orchestration, tool calls into APIs and databases mid-conversation, plus testing and call observability
Consent and trust SOC 2 Type 1 and 2, HIPAA, GDPR, CCPA and PCI compliant; self-hosting for in-house data control SOC 2, HIPAA and PCI compliance with SSO, OAuth and role-based access control; HIPAA is a $2,000 / month add-on and zero data retention $1,000 / month on both plans
MCP-ready Yes Yes
Deployment more entries Cloud (SaaS), Browser-based, On-premise Cloud (SaaS), Browser-based
Support Community forum more entries Email helpdesk, Community forum
Onboarding Documentation and knowledge base Documentation and knowledge base
Company size Small and mid-sized, Enterprise Small and mid-sized, Enterprise
Integrations Not stated OpenAI, Anthropic, Groq, Deepgram, Gladia, ElevenLabs, Salesforce, HubSpot, Zapier, Slack, Google Workspace

Compare more tools

Row where the values differ The small markers point at the lower number, the longer list or the stated feature. They describe the data, they are not a verdict.

The short version

Key Differences

  • Starting price Deepgram Usage-based, pay-as-you-go Vapi From $0.05 / minute of calls
  • Deployment Deepgram Cloud (SaaS), Browser-based, On-premise Vapi Cloud (SaaS), Browser-based
  • Support Deepgram Community forum Vapi Email helpdesk, Community forum
  • Output Deepgram Speech-to-text, text-to-speech and voice agents Vapi Voice agents for inbound and outbound phone calls, web voice, and SMS or chat
  • API Deepgram Yes Vapi Yes, REST API, CLI and SDKs

Every line is one datapoint from the table above, picked automatically. Nothing here is written text.

The trade-offs

Strengths and Limitations

Deepgram

Strengths

  • Unified speech-to-text, text-to-speech and voice-agent APIs
  • Real-time streaming with low latency for live applications
  • Usage-based with $200 free credit and no card required
  • Runs self-hosted for data control and compliance

Limitations

  • Developer platform, not a consumer voice studio
  • Several headline per-minute rates are promotional and sit below the list price, so the long-run cost depends on which rate applies

Vapi

Strengths

  • Per-minute pricing with model provider costs passed through at cost
  • Bring your own provider keys and the pass-through drops to nothing
  • Free choice of speech-to-text, model and voice provider across dozens of options
  • Official MCP server lets external AI agents drive Vapi's APIs

Limitations

  • HIPAA compliance and zero data retention are monthly add-ons rather than included
  • Total cost depends on which model, transcription and voice providers you choose
  • Concurrent lines beyond the first ten cost $10 per month each
  • A platform to build on, not a finished call-centre product

Plans

Pricing

Deepgram

  • Pay As You Go $0.0048 Per minute of Nova-3 monolingual streaming speech-to-text at the current promotional rate, $0.0077 at list. Nova-3 multilingual $0.0058, Flux English $0.0065. Text-to-speech $0.0150 / 1,000 characters on Aura-1 and $0.030 on Aura-2. Voice Agent API from $0.056 / minute. Add-ons are priced separately: redaction and diarization $0.0020 / minute each, entity detection $0.0017, keyterm prompting $0.0013. No minimums, no expiry, $200 in credits to start without a card.
  • Growth From $4,000 Per year in prepaid credits, redeemed against usage at lower rates: Nova-3 monolingual streaming $0.0042 / minute, Aura-1 $0.0135 and Aura-2 $0.027 / 1,000 characters.
  • Enterprise Not stated Custom pricing, volume commitments, self-hosting and dedicated support.
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Vapi

  • Build $0.05 Per minute of calls, usage-based, plus $0.005 per SMS or chat message. Ten call concurrency included, additional lines $10 / month each. Model provider costs at cost. Community Discord and email support.
  • Scale Not stated Annual contract with a fixed platform fee and committed volume, volume-based per-minute pricing on quote, enterprise features including SOC 2, HIPAA and PCI, a dedicated account team and a custom support SLA.
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What users say

Review Scores · opens after launch

Deepgram

Ease of use
Not rated yet
User interface
Not rated yet
Onboarding
Not rated yet
Support and service
Not rated yet
Value for money
Not rated yet
Features
Not rated yet

No reviews yet. Be the first to review this tool. Every review is checked for fairness before it appears, and the vendor cannot have one removed.

Vapi

Ease of use
Not rated yet
User interface
Not rated yet
Onboarding
Not rated yet
Support and service
Not rated yet
Value for money
Not rated yet
Features
Not rated yet

No reviews yet. Be the first to review this tool. Every review is checked for fairness before it appears, and the vendor cannot have one removed.

Where this comes from

Where this comes from

Deepgram https://deepgram.com · checked against the official source on 2026-09-01

Vapi https://vapi.ai · checked against the official source on 2026-08-30

This table lists factual criteria taken from information the vendors publish themselves. For how we put it together, see the methodology.