Vapi and Retell AI are the two developer platforms most teams shortlist when building AI voice agents, and they are separated by a whisker on our rubric – Vapi 8.1, Retell 8.2. Both are model-agnostic, both give you a visual flow builder plus an API, and both bill per minute. The difference is emphasis: Vapi goes deepest on flexibility, Retell goes furthest on proof and polish. Here is how they compare, criterion by criterion.
Vapi vs Retell AI at a glance
| Vapi | Retell AI | |
|---|---|---|
| Our score | 8.1/10 | 8.2/10 |
| Base price | $0.05/min | $0.07/min |
| Real all-in | ~$0.30/min | ~$0.13-0.31/min |
| Latency | ~500-900ms (config-dependent) | ~600ms consistent |
| Best for | Maximum build flexibility | Best-rated production platform |
| Setup | Code-first + dashboard | No-code flow builder + API |
How they score on our rubric
We score every platform from 1 to 10 on six weighted criteria (see our methodology). Here is how Vapi and Retell compare on each.
| Criterion (weight) | Vapi | Retell AI | Winner |
|---|---|---|---|
| Voice quality & latency (25%) | 8.0 | 8.5 | Retell AI |
| Build power & flexibility (20%) | 9.0 | 8.0 | Vapi |
| Integrations & telephony (15%) | 8.5 | 8.5 | Tie |
| Ease of setup (15%) | 6.5 | 8.0 | Retell AI |
| Value (15%) | 8.0 | 7.5 | Vapi |
| Reliability & scale (10%) | 8.5 | 9.0 | Retell AI |
| Weighted total | 8.1 | 8.2 | Retell AI |
Retell edges the total on reliability (9.0 vs 8.5) and ease of setup, while Vapi wins build power (9.0 vs 8.0) and matches on integrations. The gap is small and comes down to whether you value raw flexibility or proven polish.
Where Vapi wins
Vapi has the deepest build flexibility on our list. You can mix any speech-to-text, LLM and text-to-speech, bring your own API keys to cut component costs to provider price, and its base fee is the cheapest at $0.05/min. Its SDK, CLI and MCP coverage is the broadest, and its enterprise proof is unmatched – Amazon Ring routes its inbound calls through Vapi, chosen over 40 rivals. Read the full Vapi review.
Where Retell wins
Retell is the most-trusted platform in the category for production use and delivers consistent ~600ms latency with clean turn-taking. Its visual Conversation Flow builder makes structured call design more approachable, and reported traction near $50M ARR signals real production use. For most teams shipping a contact-center agent, it is the safer default. Read the full Retell AI review.
Which should you choose?
- Choose Vapi if you want maximum control, the cheapest base rate and the deepest model flexibility, and you have engineering resource to tune the stack.
- Choose Retell if you want the best-rated, most polished production platform with consistent low latency and less tuning.
- Either way you stay model-agnostic and pay per minute, so estimate your real all-in cost at volume before you commit.
Pricing compared
Both bill per minute, but the real cost depends on volume and models. Vapi’s base is $0.05/min and Retell’s $0.07/min, yet both add speech-to-text, LLM and telephony on top, so the realistic all-in for either lands around $0.13-0.31/min depending on the model you choose. Vapi can be cheaper if you bring your own API keys and tune the stack; Retell’s voice-infrastructure rate is simpler to predict. For low volume, either free allowance is enough to test; at high volume, model the LLM cost carefully, since it often dwarfs the platform fee.
Features compared
Both give you a visual flow builder, function calling into your tools, and bring-your-own-LLM. Vapi goes deeper on flexibility – 14 or more text-to-speech providers, the broadest SDK coverage, a CLI and an MCP server – which suits teams building something custom. Retell focuses on production polish: a clean Conversation Flow builder, simulation testing before launch, and strong telephony with warm transfer for contact centres. If you want to assemble a bespoke stack, choose Vapi; if you want a proven path to a live support or sales agent, choose Retell.
Getting started
Both let you spin up a first agent quickly. Vapi’s CLI and templated SDK quickstarts make it fast for developers, though the dashboard has a learning curve; Retell’s dashboard and simulation testing make structured call flows approachable for semi-technical teams, and reviewers cite good docs. If your team is engineering-heavy, either is quick to start; if it is not, Retell’s guardrails and testing tools shorten the path to a reliable agent.
Verdict
It is a near-tie: Retell (8.2) is the safer, best-rated default with consistent latency, while Vapi (8.1) is the pick for teams that want maximum flexibility and the lowest base cost. Both are excellent. See how they rank against the full field in our best AI voice agents guide.
Related AI voice agent guides
Keep comparing across our AI voice agent cluster: Vapi vs Bland AI, Best Vapi alternatives and Best Retell AI alternatives.
Frequently Asked Questions
Is Vapi or Retell better?
They are nearly tied on our rubric – Retell scores 8.2 to Vapi’s 8.1. Retell is better for a best-rated, polished production platform with consistent ~600ms latency; Vapi is better for maximum build flexibility and the cheapest base rate ($0.05/min). Both are model-agnostic developer platforms.
Is Vapi cheaper than Retell?
Vapi’s base fee is lower ($0.05/min vs Retell’s $0.07/min), but both bill speech-to-text, LLM and telephony separately, so real all-in pricing lands around $0.13-0.31/min for each depending on the models you choose. Bringing your own API keys lowers the cost on both.
Which has lower latency, Vapi or Retell?
Retell is more consistent at roughly 600ms end-to-end. Vapi’s latency depends on the models you pick – a well-tuned stack is around 550ms, but real-world voice-to-voice is often 500-900ms with occasional spikes. Test both with your own configuration.
Do Vapi and Retell support bring-your-own LLM?
Yes, both are model-agnostic. Vapi lets you use any LLM (OpenAI, Anthropic, Google or custom) and bring your own API keys; Retell supports GPT, Claude, Gemini or a custom LLM via WebSocket. That flexibility is a core reason developers pick either.
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