benchrAll capabilities Image, audio and video
Talk to it out loud and hear it answer
Not transcribe-then-answer-then-synthesise. One session on gpt-realtime-2.1 where audio goes in and audio comes back, with the turn-taking handled for you.
DocsOfficially documentedTestNot tested by benchr
OpenAI API
Overview
- Runs over three transports: WebRTC for browser and mobile clients, WebSocket for server-side pipelines, and SIP for telephony.
- Removes the stitched pipeline, which is what removes most of the latency people notice in voice agents.
- Exposes reasoning effort as a knob, so a production voice agent can be tuned for responsiveness.
How it works
- 01Pick the transport by where the audio lives - browser to WebRTC, server to WebSocket, phone number to SIP.
- 02Start with reasoning effort set to low, which the documentation names as the production starting point for voice agents.
- 03Tune the transcription delay setting deliberately: lower delay gives earlier partial text, higher delay improves transcript quality.
- 04Design the interruption behaviour before the prompt. Barge-in is the difference between a demo and something people will use.
Limits
- It is a session protocol, not a request-response endpoint - reconnection, state and audio buffering are your responsibility.
- The latency and quality trade-off is explicit in the documentation and cannot be optimised away, only chosen.
- Telephony via SIP puts you inside carrier constraints the model documentation does not cover.
Verification
benchr test runs
benchr has not run this capability. No test has been published.
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Evidence
Sources
- OpenAI - Realtime API: gpt-realtime-2.1, WebRTC / WebSocket / SIP, reasoning effort guidance Tier 1 · September 1, 2026
Not stated by the source
- End-to-end latency figures for any transport
- Concurrency limits per organisation
Source-check history
- September 1, 2026DocsOfficially documentedFirst logged. Model id, the three transports and the low-reasoning-effort production guidance read from the realtime guide.