Is Avencera cheaper than pyannoteAI?

Yes. Avencera transcribes from $0.06 an hour, or $0.07 with speaker labels. At 100 hours a month with speaker labels, pyannoteAI STT Orchestration costs $21.27 against $7.00 at Avencera, 3.0× as much.

Does Avencera use pyannote?

Yes. Avencera labels speakers with speakrs, our open-source Rust port of pyannote’s community-1 pipeline, which matches pyannote’s published error rates. pyannoteAI’s paid Precision models are more accurate than community-1.

Do Avencera and pyannoteAI transcribe with the same model?

They can. pyannoteAI’s STT Orchestration runs NVIDIA Parakeet v3 by default, the same model as Avencera’s v3 offers, so the words should match; the speaker labels are where they differ.

Can I buy speaker labels without a transcript from Avencera?

Yes. Avencera sells community-1 speaker labels on their own for $0.02 an hour, with prepaid credit and no plan. A transcript with speaker labels costs $0.07 an hour.

How do I switch from pyannoteAI to Avencera?

Avencera uses OpenAI’s transcription API format, so any OpenAI SDK works. Send the same audio files you send pyannoteAI, and map its response fields to the OpenAI-style transcript.

pyannoteAI alternative for speaker diarization: Avencera vs pyannoteAI

For speaker labels alone, pyannoteAI’s Community-1 costs 2.0× as much as Avencera, on plans from $21.27 a month. At 100 hours a month with speaker labels, pyannoteAI STT Orchestration costs 3.0× as much as Avencera. Precision-3 makes fewer speaker errors on all 10 recording types in pyannoteAI’s benchmark.

By Praveen Perera. Prices and features checked October 23, 2026.

At a glance

pyannoteAI is the company behind pyannote, the open-source speaker diarization toolkit, and diarization is its focus: it sells speaker labels on their own, with transcription as an add-on. Its STT Orchestration product pairs NVIDIA Parakeet v3, the same transcription model Avencera runs, with its paid Precision diarization models. Avencera labels speakers with pyannote’s open community-1 model and sells them on their own or with a transcript.

Feature	Avencera	pyannoteAI
Transcript, at 100 hours a month	$0.06 an hour	STT Orchestration: $0.213 an hour, Developer plan (3.5×)
With speaker labels, at 100 hours a month	$0.07 an hour	STT Orchestration: $0.213 an hour, Developer plan (3.0×)
Speaker labels	Included in the speaker transcript price	STT Orchestration: included
Speaker labels without a transcript	$0.02 an hour, no plan	Community-1: $0.039 an hour (2.0×)Precision-3: $0.125 an hour (6.3×)On plans from $21.27 a month
Billing	Prepaid credit, no subscription	STT Orchestration: Developer from $21.27 a month, or Starter from $110.81 a month
Real-time streaming	No, recorded audio only	Live speaker labels with Live-1, but no live transcripts
Self-hosting	Open models you can run yourself	Self-hosted Precision models on Enterprise plans
API	OpenAI-compatible	pyannoteAI’s own

Price with speaker labels

Audio a month	Avencera	pyannoteAI STT Orchestration
10 hours	$0.70	$21.27 30×
100 hours	$7.00	$21.27 3.0×
1,000 hours	$70.00	$161.18 2.3×
10,000 hours	$700.00	$1,611.79 2.3×

See every provider at any volume on the pricing page.

Accuracy

Speaker labels

pyannoteAI Precision-3 makes fewer speaker errors than Avencera on all 10 recording types in pyannoteAI’s benchmark. Averaged across them, the diarization error rate is 23.5% for Avencera and 16.9% for Precision-3. In the same benchmark, Avencera’s speaker labels make fewer errors than AssemblyAI, Speechmatics, Soniox, ElevenLabs and Deepgram on every recording type.

Diarization error rate by recording type, lower is better

Radio interviews 12 recordings, 3 or 4 speakers

Precision-3 by 2.4 points

Avencera community-1: 10.4%. pyannoteAI Precision-3: 8.0%.
Clinical interviews 51 recordings, 2 or 3 speakers

Precision-3 by 9.2 points

Avencera community-1: 23.5%. pyannoteAI Precision-3: 14.3%.
Courtroom 12 recordings, 3 to 9 speakers

Precision-3 by 7.3 points

Avencera community-1: 11.6%. pyannoteAI Precision-3: 4.3%.
Phone calls 61 recordings, 2 speakers

Precision-3 by 4.4 points

Avencera community-1: 12.2%. pyannoteAI Precision-3: 7.8%.
Task dialogues 19 recordings, 2 speakers

Precision-3 by 5.6 points

Avencera community-1: 10.1%. pyannoteAI Precision-3: 4.5%.
Meetings 11 recordings, 3 to 6 speakers

Precision-3 by 6.3 points

Avencera community-1: 36.4%. pyannoteAI Precision-3: 30.1%.
Restaurant conversations 12 recordings, 4 to 8 speakers

Precision-3 by 12.9 points

Avencera community-1: 51.0%. pyannoteAI Precision-3: 38.1%.
Field interviews 22 recordings, 2 or 3 speakers

Precision-3 by 6.8 points

Avencera community-1: 18.2%. pyannoteAI Precision-3: 11.4%.
Lab interviews 12 recordings, 2 speakers

Precision-3 by 8.2 points

Avencera community-1: 14.1%. pyannoteAI Precision-3: 5.9%.
Web video 35 recordings, 1 to 7 speakers

Precision-3 by 3.1 points

Avencera community-1: 47.8%. pyannoteAI Precision-3: 44.7%.

Choose pyannoteAI if

You need the most accurate speaker labels. Precision-3 makes fewer errors on all 10 recording types in pyannoteAI’s benchmark, 16.9% against 23.5% on average.
You want to start free. pyannoteAI has a 30-day free trial.
You want speaker identification from voiceprints, or streaming diarization with Live-1.
You need an API today. Avencera opens soon.

Choose Avencera if

You want the lower bill. pyannoteAI STT Orchestration costs 3.0× as much at 100 hours a month with speaker labels.
You only need speaker labels. Avencera sells them on their own for $0.02 an hour; pyannoteAI’s Community-1 costs $0.039 an hour, on plans from $21.27 a month.
You want prepaid credit with no subscription, no minimum and no expiry.
You’d like to run the same stack yourself one day. Avencera’s speaker labels come from speakrs, our open-source Rust port of community-1.
Your audio stays yours. Avencera deletes it once the transcript is ready and never trains on it.

Switching to Avencera

Avencera serves OpenAI’s transcription API, so the official OpenAI SDKs work with a new base URL and model name. Set speaker_labels to true for a speaker on every segment.

from openai import OpenAI

client = OpenAI(base_url="https://api.avencera.com/v1", api_key="YOUR_AVENCERA_KEY")

with open("meeting.mp3", "rb") as audio:
    transcript = client.audio.transcriptions.create(
        model="avencera/parakeet-tdt-0.6b-v2",
        file=audio,
        extra_body={"speaker_labels": True},
    )

Questions

Is Avencera cheaper than pyannoteAI?: Yes. Avencera transcribes from $0.06 an hour, or $0.07 with speaker labels. At 100 hours a month with speaker labels, pyannoteAI STT Orchestration costs $21.27 against $7.00 at Avencera, 3.0× as much.
Is Avencera more accurate than pyannoteAI?: pyannoteAI Precision-3 makes fewer speaker errors than Avencera on all 10 recording types in pyannoteAI’s benchmark. Averaged across them, the diarization error rate is 23.5% for Avencera and 16.9% for Precision-3. In the same benchmark, Avencera’s speaker labels make fewer errors than AssemblyAI, Speechmatics, Soniox, ElevenLabs and Deepgram on every recording type.
Does Avencera use pyannote?: Yes. Avencera labels speakers with speakrs, our open-source Rust port of pyannote’s community-1 pipeline, which matches pyannote’s published error rates. pyannoteAI’s paid Precision models are more accurate than community-1.
Do Avencera and pyannoteAI transcribe with the same model?: They can. pyannoteAI’s STT Orchestration runs NVIDIA Parakeet v3 by default, the same model as Avencera’s v3 offers, so the words should match; the speaker labels are where they differ.
Can I buy speaker labels without a transcript from Avencera?: Yes. Avencera sells community-1 speaker labels on their own for $0.02 an hour, with prepaid credit and no plan. A transcript with speaker labels costs $0.07 an hour.
How do I switch from pyannoteAI to Avencera?: Avencera uses OpenAI’s transcription API format, so any OpenAI SDK works. Send the same audio files you send pyannoteAI, and map its response fields to the OpenAI-style transcript.