CekuraBench

AssemblyAI Universal 3.6 Pro

Every modelAssemblyAI

Accuracy vs. speed

Lower and further left is better

Best quadrantBest picks
Final-text delay P50 (ms)
Pipecat Dataset WER (%)

AssemblyAI Universal 3.6 Pro is 1st of 19 on the Pipecat Dataset and 14th of 19 on the Ocular Dataset.

1.77% Pipecat WER (1st) · 4.50% Ocular WER (14th) · 485ms First text (1st) · 91ms Final text (3rd)Likely range, 95% confidence: Pipecat WER 1.55 to 2.00%, Ocular WER 3.66 to 5.34%Published price $0.45 per hour of streamed audio. Pay as you go, billed while the session is open. Source, checked Oct 8, 2026.

Last updated Methodology by Dileep Chagam

AssemblyAI Universal 3.6 Pro against every other model

Lower is better on every measure. Hover a column for that model's full numbers.

  1. 1.8%
    Universal 3.6 Pro
  2. 1.9%
    Universal 3.5 Pro
  3. 2.0%
    Scribe Pro
  4. 2.0%
    Scribe
  5. 2.0%
    Chirp 3
  6. 2.1%
    Reson8
  7. 2.2%
    Realtime Whisper
  8. 2.4%
    Ink 2
  9. 2.5%
    Linden
  10. 2.5%
    STT-RT v5
  11. 2.6%
    Chirp 2
  12. 2.7%
    STT-1
  13. 3.4%
    4o Mini Transcribe
  14. 3.5%
    Nova-3
  15. 3.7%
    Pulse
  16. 3.9%
    4o Transcribe
  17. 3.9%
    Flux English
  18. 5.0%
    Flux Multilingual
  19. 6.5%
    Gradium
Glossary: WER, TTFT, TTFS, P50
WER · Word error rate
Share of words the model got wrong: replaced, missing or added. Lower is better.
Pipecat Dataset
1,000 short public clips from Pipecat's STT benchmark dataset.
Ocular Dataset
8 recordings from 4 real phone conversations, licensed from Ocular.
Likely range · 95% range
Where the model's true score probably falls, given how much audio was tested. Overlapping ranges are too close to call.
TTFT · Time to first text
How long after the audio starts streaming until the first words appear.
TTFS · Final-text delay
How long after the caller stops until the full transcript arrives. A voice agent waits for this before it replies.
P50 / P90 / P95 · Typical, slow and slowest turns
Half of turns are faster than P50. Only 1 in 10 is slower than P90, and 1 in 20 slower than P95.

Where AssemblyAI Universal 3.6 Pro struggled

On real calls, dropped words are its biggest source of error. On clean clips, wrong words lead.

Wrong words

What the speaker said, with AssemblyAI Universal 3.6 Pro's mistakes marked: I just received a suspicious text message that claims my bank account has been locked due to some suspicious activity and it includes a strange link but I'm hesitant written as I mess it up

Everything AssemblyAI Universal 3.6 Pro wrote

I just received a suspicious text message that claims my bank account has been locked due to some suspicious activity. And it includes a strange link. But I mess it up.

Pipecat Dataset clip pipecat-ee49bba6-ad9f-6328-8d52-87700558bc9f

Wrong words

What the speaker said, with AssemblyAI Universal 3.6 Pro's mistakes marked: Please add organic kale written as Gala, apples, 2% whole milk, and a loaf of sourdough written as sort of bread to my main shopping list

Everything AssemblyAI Universal 3.6 Pro wrote

Please add organic Gala apples, 2% whole milk, and a loaf of sort of bread to my main shopping list.

Pipecat Dataset clip pipecat-e531272b-cdf6-5862-9400-1f439f03af13

Marked: words AssemblyAI Universal 3.6 Pro left out or got wrong. Audio from the Pipecat Dataset, under CC BY 4.0, re-encoded as MP3.

TTFT and TTFS at P50, P90 and P95

Timed on the same 206 streamed Ocular turns as every other model. P90 and P95 show what a caller meets on a slow turn.

TTFS, final text

How long after the caller stops until the full transcript arrives. A voice agent waits for this before it replies.

20ms100ms500ms2s
Typical, P50
91ms
3rd fastest of 19
Slow, P90
210ms
8th fastest of 19
Slowest, P95
232ms
8th fastest of 19

TTFT, first text

How long after the audio starts streaming until the first words appear.

200ms1s5s20s
Typical, P50
485ms
Fastest of 17
Slow, P90
966ms
Fastest of 17
Slowest, P95
967ms
Fastest of 17

Every other model's typical turn, on the same axis.

1,000 Pipecat clips · 8 Ocular recordings · 206 turns timed · 0 failed requests

AssemblyAI Universal 3.6 Pro head to head

Every comparisonAll 19 modelsBenchmark source

AssemblyAI Universal 3.6 Pro FAQ

  • AssemblyAI Universal 3.6 Pro places highest on the Pipecat Dataset, 1st of 19 at 1.77%. Its weakest placing is the Ocular Dataset, 14th of 19 at 4.50%.

  • AssemblyAI Universal 3.6 Pro transcribes the 1,000 public Pipecat clips at 1.77% word error rate and the eight licensed Ocular recordings at 4.50%. Word error rate counts incorrect, missing, and extra words against the reference transcript, so lower is better.

  • First text arrives after 485ms at the median, and the transcript is final 91ms after the speaker stops. Both are measured on the same 206 streamed turns as every other model, and the page shows P90 and P95 as well, which is what a caller meets on a bad turn.

  • Every model runs the same two datasets under the same conditions: 1,000 public clips from Pipecat's STT benchmark dataset for accuracy at scale, and eight licensed conversation recordings from Ocular for real speech. Latency comes from 206 streamed turns, using each provider's own supported finalization contract. AssemblyAI Universal 3.6 Pro returned usable text for 1,000 of the public clips.