CekuraBench
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OpenAICascade baseline

GPT-Live 1 + GPT-6 Sol (low thinking) vs Flux → GPT-4.1 → ElevenLabs Flash

Flux → GPT-4.1 → ElevenLabs Flash is ahead on reliability, success rate, data accuracy, stalled calls and interruption, and GPT-Live 1 + GPT-6 Sol (low thinking) on agent responses and response time.

Last updated Methodology by Dileep Chagam

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Success rate by suite

Higher is better
Appointments59 scenariosMedicare23 scenarios
  • GPT-Live 1 + Sol lowOpenAI
    97%
    49%
  • Cascade, GPT-4.1Not ranked
    97%
    83%
Each model's share of calls that passed every check, on each suite.
Verdict

Which to pick

Pick GPT-Live 1 + GPT-6 Sol (low thinking) for getting the agent's replies right (0.8 points higher) and fast replies (0.15s sooner). Pick Flux → GPT-4.1 → ElevenLabs Flash for reliability across repeated calls (7.3 points higher), calls that pass every check (9.3 points higher), saving the caller's data correctly (5.1 points higher), fewer stalled calls (11.4 points lower) and handling interruptions (0.07 higher).

Every metric, side by side

Reliability

Scenarios that passed on all three runs.

GPT-Live 1 + Sol low
75.6%2nd
Cascade, GPT-4.1
82.9%

Cascade, GPT-4.1, 7.3 points higher

Success rate

Calls that passed every check.

GPT-Live 1 + Sol low
83.7%3rd
Cascade, GPT-4.1
93.1%

Cascade, GPT-4.1, 9.3 points higher

Agent responses

Calls where the agent's replies reached the expected outcome.

GPT-Live 1 + Sol low
100.0%1st
Cascade, GPT-4.1
99.2%

GPT-Live 1 + Sol low, 0.8 points higher

Data accuracy

Calls where everything the agent saved matched exactly.

GPT-Live 1 + Sol low
89.0%2nd
Cascade, GPT-4.1
94.1%

Cascade, GPT-4.1, 5.1 points higher

Stalled calls

Calls where the agent went silent for 10 seconds or more.

GPT-Live 1 + Sol low
12.2%11th
Cascade, GPT-4.1
0.8%

Cascade, GPT-4.1, 11.4 points lower

Interruption

How well it handled being talked over, 0 to 5.

GPT-Live 1 + Sol low
4.8910th
Cascade, GPT-4.1
4.96

Cascade, GPT-4.1, 0.07 higher

Response time

Median time to start replying after the caller finishes.

GPT-Live 1 + Sol low
2.02s6th
Cascade, GPT-4.1
2.17s

GPT-Live 1 + Sol low, 0.15s sooner

Cost / min

One minute of call at the vendor's published rates.

GPT-Live 1 + Sol low
$0.0552nd
Cascade, GPT-4.1
No verified rate

Not comparable

The small figure is the place among ranked models. The cascade is not ranked.

GPT-Live 1 + Sol low answers first

GPT-Live 1 + Sol low 2.02s, Cascade, GPT-4.1 2.17s at the median.

Response time, median to p90

Lower is betterMedianTo p90
Medianp90
  • GPT-Live 1 + Sol lowOpenAI
    GPT-Live 1 + Sol low: median 2.02s, p90 2.42s
    2.02s2.42s
  • Cascade, GPT-4.1Not ranked
    Cascade, GPT-4.1: median 2.17s, p90 2.51s
    2.17s2.51s
2.0s3.0s
Seconds from the caller finishing to the agent starting to reply, per model.

What we saw on the calls

GPT-Live 1 + GPT-6 Sol (low thinking)

  • Near perfect on bookings, run after run.
All 4 notes on GPT-Live 1 + Sol low
Model
gpt-live-1
Setting
Delegates reasoning and tools to Sol
Voice
marin
Turn taking
Service turn detection
Audio
24 kHz
Cost
Includes the delegated backend model.

Flux → GPT-4.1 → ElevenLabs Flash

  • Most scenarios pass every run, and none fails every run.
All 4 notes on Cascade, GPT-4.1
Model
flux-general-en → gpt-4.1 → eleven_flash_v2_5
Setting
No reasoning setting
Voice
ElevenLabs 21m00Tcm4TlvDq8ikWAM
Turn taking
Speech-to-text turn detection
Audio
16 kHz
Cost
Not published: no verified combined rate for the three services.
See the full leaderboardReference agent

Related comparisons

Frequently asked questions

Is GPT-Live 1 + GPT-6 Sol (low thinking) or Flux → GPT-4.1 → ElevenLabs Flash more reliable?

Flux → GPT-4.1 → ElevenLabs Flash is more reliable, by 7.3 points. GPT-Live 1 + GPT-6 Sol (low thinking) passed 62 of 82 scenarios on all three runs, and Flux → GPT-4.1 → ElevenLabs Flash passed 68. A scenario only counts when every run of it passed.

Is GPT-Live 1 + GPT-6 Sol (low thinking) better than a cascaded STT, LLM and TTS pipeline?

On reliability, no: the Flux → GPT-4.1 → ElevenLabs Flash cascade passes more scenarios on every run. Flux → GPT-4.1 → ElevenLabs Flash is ahead on reliability, success rate, data accuracy, stalled calls and interruption, and GPT-Live 1 + GPT-6 Sol (low thinking) on agent responses and response time. Both ran as the same agent, with the same prompt and tools.

Which saves caller data more accurately, GPT-Live 1 + GPT-6 Sol (low thinking) or Flux → GPT-4.1 → ElevenLabs Flash?

Flux → GPT-4.1 → ElevenLabs Flash, by 5.1 points. GPT-Live 1 + GPT-6 Sol (low thinking) saved everything exactly right on 89.0% of the calls that save data, and Flux → GPT-4.1 → ElevenLabs Flash on 94.1%. On Appointments, 100.0% against 98.8%. On Medicare, 60.6% against 81.8%. A call counts only when nothing is missing, wrong, extra or saved twice.

Is GPT-Live 1 + GPT-6 Sol (low thinking) faster than Flux → GPT-4.1 → ElevenLabs Flash?

Yes. GPT-Live 1 + GPT-6 Sol (low thinking) starts replying 0.15s sooner at the median. GPT-Live 1 + GPT-6 Sol (low thinking) takes 2.02s at the median and 2.42s at p90; Flux → GPT-4.1 → ElevenLabs Flash takes 2.17s and 2.51s. Both are measured on the call audio, from the caller finishing to the agent starting to reply.

Which handles interruptions better, GPT-Live 1 + GPT-6 Sol (low thinking) or Flux → GPT-4.1 → ElevenLabs Flash?

Flux → GPT-4.1 → ElevenLabs Flash, by 0.07 on a 0 to 5 scale. GPT-Live 1 + GPT-6 Sol (low thinking) scores 4.89 and Flux → GPT-4.1 → ElevenLabs Flash 4.96 for how well the agent handled being talked over.

Which goes silent on callers less often, GPT-Live 1 + GPT-6 Sol (low thinking) or Flux → GPT-4.1 → ElevenLabs Flash?

Flux → GPT-4.1 → ElevenLabs Flash, by 11.4 points. The agent went silent for 10 seconds or more on 12.2% of GPT-Live 1 + GPT-6 Sol (low thinking) calls and 0.8% of Flux → GPT-4.1 → ElevenLabs Flash calls.

Which is cheaper, GPT-Live 1 + GPT-6 Sol (low thinking) or Flux → GPT-4.1 → ElevenLabs Flash?

There is no verified per-minute rate for Flux → GPT-4.1 → ElevenLabs Flash, so cost cannot be compared yet.

Where does the GPT-Live 1 + GPT-6 Sol (low thinking) vs Flux → GPT-4.1 → ElevenLabs Flash data come from?

Cekura ran both as the whole agent in the same open-source Pipecat pipeline, with the same prompt, tools and connection. A simulated caller worked through all 82 scenarios on live calls, three times each, 2,952 calls across the benchmark. A call passes only when the agent said the right things and saved the right data. The cascade runs the same agent for reference and is never ranked.