Do coding agents recommend Retell AI?
Retell AI was chosen in 18% of 308 judged voice agents sessions, ranking second. Measured with Claude Code, Codex and Cursor.
Retell AI was chosen in 18% of 308 judged voice agents sessions, ranking second. It was also raised as a candidate in 110 further sessions without being chosen.
This page reports what happened when Claude Code, Codex and Cursor had to solve a problem in voice agents inside a realistic codebase. Not what a chat assistant says about Retell AI. What an agent actually installed.
The numbers
| Category | Voice agents |
| Sessions in the category | 308 |
| Sessions where Retell AI was chosen | 55 |
| Install share | 18% |
| Rank in category | 2 of 18 |
| Codebases it won in | 8 |
| Raised as a candidate, not chosen | 110 |
| Chosen when considered | 33% |
| Site | retellai.com |
By agent
The three agents land within 12 points of each other on Retell AI, which is closer than most products in this experiment manage.
| Agent | Sessions | Chose Retell AI | Share |
|---|---|---|---|
| Claude Code | 94 | 12 | 13% |
| Codex | 110 | 28 | 25% |
| Cursor | 104 | 15 | 14% |
By who was asking
Retell AI does much better with one kind of buyer than another. It won 32% of sessions asked as vibe coder and 7% of those asked as enterprise team.
| Who is asking | Sessions | Chose Retell AI | Share |
|---|---|---|---|
| Vibe coder | 62 | 20 | 32% |
| Junior developer | 42 | 4 | 10% |
| Senior engineer | 128 | 26 | 20% |
| Enterprise team | 76 | 5 | 7% |
What Retell AI was up against
The full ranking in voice agents, from the same sessions:
| # | Product | Runs won | Share |
|---|---|---|---|
| 1 | Vapi | 74 | 24% |
| 2 | Retell AI (this page) | 55 | 18% |
| 3 | OpenAI Realtime API | 37 | 12% |
| 4 | LiveKit Agents | 35 | 11% |
| 5 | ElevenLabs Agents | 30 | 10% |
| 6 | Twilio ConversationRelay | 28 | 9% |
| 7 | Built in-house (no product adopted) | 18 | 6% |
| 8 | Azure Voice Live API | 10 | 3% |
What this means
A solid second or third position in a category means the agent is genuinely choosing rather than reaching automatically. That is a winnable position, because the inputs it uses can be changed.
The fastest gains are usually in the sessions that were nearly won: read them, find the step where the agent moved on, and fix that step.
Where these numbers come from
The 308 sessions in voice agents are part of a published set of 5,292, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.
Every voice agents run can be replayed on the board.
If you work on Retell AI: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.
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Common questions
Do coding agents recommend Retell AI?
Yes. Retell AI was chosen in 55 of the 308 judged sessions in voice agents, a 18% install share, ranking second in its category.
Does Claude Code recommend Retell AI?
In 12 of the 94 sessions in voice agents run with Claude Code, which is 13%.
Do different coding agents treat Retell AI differently?
Yes, and by a wide margin. Codex chose it in 25% of its runs and Claude Code in 13%.
How was this measured?
Real coding agents at pinned versions were run in sandboxes inside 51 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind.
How often is Retell AI considered but not chosen?
It was raised as a candidate in 110 sessions without being chosen, and chosen in 55. That is a 33% conversion from considered to chosen.
Where this comes from
Armature ran 5,292 judged sessions with Claude Code, Codex and Cursor inside 51 realistic codebases, and published every run. The numbers on this page come from that work.