CekuraBench

Compare speech-to-speech (S2S) benchmarks

Any two of the 11 models, or any one against the cascade, on the same phone agent and the same calls.

Last updated Methodology by Dileep Chagam

Compare
GPT Realtime 2.1OpenAI
Flux → GPT-4.1 → ElevenLabs FlashBaseline, not ranked
Reliability
79.3%1st
82.9%
3.7 points higher
Data accuracy
92.0%1st
94.1%
2.1 points higher
Response time
1.94s5th
0.23s sooner
2.17s
Cost / min
$0.0856th
No verified rate
All suites. The small figure is the place among ranked models.All 66 comparisons

By provider

The best model from each provider, metric by metric.

Every comparison

GPT Realtime 2.1

GPT-Live 1 + Sol low

Azure Realtime

Phonic v1

Grok Think Fast 2.0

Gemini 3.1 Flash Live

Deepslate Opal

Gemini 3.8 Live Thinking

Nova 2 Sonic

Realtime 2.1 Mini

Gemini 3.8 Live

Cascade, GPT-4.1Not ranked

Questions

Speech-to-speech model comparison FAQ

How do I compare speech-to-speech models?

Choose any two models to compare repeatable reliability, task success, saved-data accuracy, stalled calls, response time, interruption handling, and cost from the same live-call benchmark.

Which metrics matter most for a realtime voice model?

Start with repeatable task reliability and response time, then check data accuracy, stalled calls, interruption handling, and cost. A fast model is not useful if it cannot complete the same scenario reliably.

Can I compare GPT Realtime with Gemini Live?

Yes. Select the tested GPT Realtime and Gemini Live versions to compare their reliability and latency on the same phone agent, prompt, tools, and caller scenarios.

What is the difference between a native speech-to-speech model and a cascade?

A native model handles audio directly. A cascade connects speech-to-text, an LLM, and text-to-speech. The comparison pages test both as the same complete agent so their practical trade-offs are visible.