ElevenLabs vs Vapi vs Retell — Voice AI Platform Comparison 2026
Side-by-side comparison of the three leading voice AI platforms in 2026 — latency, languages, pricing, integrations, and what we ship in production at Ikki.

TL;DR
After shipping voice agents to production with all three platforms, here is what we'd tell a CTO choosing today:
- ElevenLabs Conversational AI — best voice quality, 29+ languages, Studio-grade TTS. Best when voice matters more than tooling.
- Vapi — most developer-friendly orchestration, best tool calling story, opinionated stack. Best for fast iteration on complex agents.
- Retell — strongest telephony integration, lowest latency on long calls, enterprise SLAs. Best for call-center replacement.
If you want one default answer in 2026: ElevenLabs for the voice, with custom orchestration on top (LangChain or your own).
What we benchmark on
We've shipped agents in production across all three platforms. Our criteria:
- End-to-end latency (mic → transcription → LLM → TTS → speaker) measured on a stable 4G connection
- Voice quality (subjective, but consistent across our team) and language coverage
- Tool calling reliability (did the agent actually trigger the function? did arguments parse?)
- Telephony integration (SIP, Twilio, native PSTN)
- Observability (logs, transcripts, replays)
- Pricing at meaningful scale (10k minutes/month)
Voice quality and languages
ElevenLabs wins on voice realism — this is their core IP. The Conversational AI product layers a low-latency turn-taking pipeline on top of their Studio-grade TTS. In French, Spanish, and Arabic, ElevenLabs voices are noticeably more natural than what Vapi or Retell ship by default.
Vapi exposes ElevenLabs as one of several providers. So you can pick ElevenLabs voices inside Vapi — but you pay both vendors. Retell ships its own voices plus integrations with Deepgram (TTS) and a handful of others. They're competent but not at ElevenLabs level for European languages.
Verdict on voice: if multilingual realism matters, default to ElevenLabs. If you're English-only and don't care about subtle expressivity, all three are acceptable.
Latency
Measured on the same agent (a 4-tool customer support assistant) with the same model (GPT-4o), same network conditions:
| Platform | Median end-to-end | P95 |
|---|---|---|
| Vapi | ~750ms | 1.2s |
| Retell | ~800ms | 1.3s |
| ElevenLabs | ~900ms | 1.5s |
Vapi and Retell pull ahead because they own the orchestration. ElevenLabs adds a small overhead because the LLM call goes through their pipeline. In practice, all three are below the conversational threshold (≈1.2s) where users start interrupting.
Tool calling
Vapi has the most polished tool calling. You define functions, they're exposed to the LLM, results are injected back, and the agent voices the response. Retell is similar but with fewer escape hatches. ElevenLabs supports tool calling through their Conversational AI agents — works fine, slightly less ergonomic.
If your agent has more than 5 tools or needs nested function calls, our recommendation is to host the orchestration yourself (with LangGraph or a custom agent loop) and use ElevenLabs only for the voice layer. We've shipped this pattern twice now.
Telephony
Retell wins. Native SIP, Twilio, and direct PSTN connection. Their docs assume you're replacing a call center. Vapi has Twilio integration and is catching up. ElevenLabs requires you to bring your own telephony layer (Twilio, Telnyx).
Pricing at scale
For 10k minutes/month with GPT-4o as the LLM:
- Vapi: ~$1,200–1,800/month depending on voice provider markup
- ElevenLabs: ~$1,500–2,200/month, voice cost dominates
- Retell: ~$1,000–1,500/month, often the cheapest at scale
These numbers shift constantly. The point is that voice agent unit economics are getting cheaper every quarter. Don't pick on pricing alone.
What we ship at Ikki in 2026
For most clients, our default stack is:
- ElevenLabs for voice (TTS + STT in their pipeline, or Deepgram for STT if needed)
- Custom orchestration (Node.js + LangGraph or pure function-calling loop)
- Twilio or Telnyx for telephony
- Pinecone or pgvector for RAG when the agent needs domain knowledge
- Posthog for transcript review and analytics
This stack gives us the best voice quality, full control over agent behavior, and predictable scaling costs. We've shipped this for Maideo and other production deployments.
When to use each platform
- Choose Vapi if: you need to ship fast, you have 1–2 engineers, the agent logic is complex.
- Choose Retell if: you're replacing a call center, telephony is the core requirement, you need enterprise SLAs.
- Choose ElevenLabs if: voice quality is the differentiator, you want multilingual support, you're willing to write your own orchestration.
Closing thoughts
The voice AI space is moving fast — what was true six months ago isn't true today. We re-benchmark every quarter. If you're starting a voice AI project now, treat the platform choice as reversible: build your business logic in a layer you control, and treat the voice infra as swappable.
Need help shipping a voice agent? Get in touch — 15-min discovery call, we listen, then we ship.
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