If you’re choosing between Vapi and LiveKit, the real question isn’t which is better, it’s which one matches your volume, team, and architecture.
Vapi is a managed voice AI platform. You plug in your LLM, TTS, and STT, configure an assistant, and get a phone number. They handle WebRTC, turn detection, tool calling, and telephony. You pay per minute.
LiveKit is an open-source real-time communications platform with an Agents framework on top. You assemble your own STT → LLM → TTS (or use OpenAI Realtime), run it on your own infra or LiveKit Cloud, and pay for compute, not a per-minute platform fee.
That distinction drives everything: cost, latency, flexibility, and how much you build vs. configure.
Cost: Where the Economics Flip
- Vapi all-in (platform + typical Haiku / GPT-4o mini + ElevenLabs/Deepgram TTS + Deepgram STT):
- Roughly $0.23–0.35/min depending on provider mix and BYOK.
- BYOK lowers Vapi’s cut but you still pay a platform fee on top of model costs.
- LiveKit Cloud (Agents):
- Billed on worker compute, not minutes.
- In practice, for voice AI: ~$0.07–0.15/min including LLM, if workers are provisioned efficiently.
- Self-hosted LiveKit:
- No per-minute platform fee.
- You pay for VMs + LLM + TTS + STT.
- Around $0.08–0.12/min at ~10,000 minutes/month on a lean but production-ready setup.
Crossover:
- Below ~5,000–10,000 minutes/month → Vapi’s managed convenience usually wins.
- Above that → LiveKit (especially self-hosted) becomes materially cheaper, and the savings compound with scale.
Latency: When Sub-300ms Actually Matters
- Vapi: Typical end-to-end latency (user stops → agent starts) is ~400–800ms, depending on LLM and streaming/buffering.
- LiveKit + OpenAI Realtime: Can reliably hit <300ms because audio streams directly into a single realtime endpoint that handles STT + LLM + TTS in one loop.
For most business use cases (bookings, outbound, FAQs), 400ms vs 250ms is not noticeable to callers. Latency only becomes a deciding factor if you’re in high-sensitivity domains (e.g. medical intake, high-touch support) where ultra-snappy back-and-forth matters.
Developer Experience & Team Fit
Vapi (configure-first):
- Time-to-first-call: ~20 minutes via dashboard.
- Easy to connect Twilio/Vonage, configure tools, and go live.
- Great for:
- Appointment booking agents.
- CRM-integrated sales/support agents.
- Fast PoCs and client demos.
- Ideal if you don’t have strong backend/async expertise in-house.
LiveKit (code-first):
- You write Python/TypeScript agents, wire pipelines, and deploy workers.
- No dashboard-first experience; you’re building an application, not just configuring one.
- In return, you get:
- Custom audio processing.
- Multi-agent orchestration and handoffs.
- Voice + video + screenshare in the same session.
- Deep SIP integration and carrier-grade routing.
If you lack a backend dev comfortable with async Python/TS, Vapi is the realistic option. If you have that capability and care about architecture, LiveKit is worth the upfront investment.
When Vapi Is the Right Call
Choose Vapi if:
- You’re a developer-led SME and want something working this week, not next quarter.
- Your volume is <5,000–10,000 minutes/month and you’re fine with per-minute pricing.
- You’re doing PoCs / validation and don’t want to overbuild infra before you prove value.
- You want multi-provider flexibility (Deepgram, AssemblyAI, ElevenLabs, OpenAI, Anthropic, Groq, etc.) via config rather than code.
Vapi is essentially: “Let us run the voice infra; you focus on prompts, tools, and integrations.”
When LiveKit Is the Right Call
Choose LiveKit if:
- You’re at 10,000–20,000+ minutes/month or expect to get there soon.
- You need SIP telephony at scale with fine-grained control.
- You’re building voice + video or multi-participant real-time experiences.
- You want multi-agent pipelines (triage → billing → technical support) with programmatic routing.
- You have self-hosting / data residency / compliance requirements that rule out a fully managed middleman.
LiveKit is: “Build your own voice AI stack on top of battle-tested RTC infra, and own the architecture and economics.”
Where Retell AI Fits
Retell AI is the third major option:
- Best when you need:
- No-code / low-code flow editor for conversation design.
- HIPAA compliance and a BAA out of the box.
- Clear, auditable state-machine-style conversation paths.
- Good fit for regulated industries with non-technical conversation designers.
Rule of thumb:
- Retell → regulated + flow-based + non-technical designers.
- Vapi → dev teams, API-first, moderate volume.
- LiveKit → scale, SIP, self-hosting, and architectural control.
Practical Recommendation
- Start on Vapi if: