Soniox alternative: Avencera vs Soniox

At 100 hours a month with speaker labels, Soniox Async costs 1.4× as much as Avencera. Avencera’s speaker labels make fewer errors on all 10 recording types in pyannoteAI’s benchmark. Soniox transcribes words more accurately on the one published test that covers both, by up to 0.7 points.

At a glance

Soniox bills its async model by tokens, which works out close to Avencera’s price per hour, with speaker labels included. It covers 60+ languages and scores well on independent tests.

FeatureAvenceraSoniox
Transcript, at 100 hours a month$0.06 an hourAsync: $0.10 an hour (1.6×)
With speaker labels, at 100 hours a month$0.07 an hourAsync: $0.10 an hour (1.4×)
Speaker labelsIncluded in the speaker transcript priceAsync: included
BillingPrepaid credit, no subscriptionAsync: pay as you go
Real-time streamingNo, recorded audio onlyYes
LanguagesEnglish with Parakeet v2, 25 European languages with v360+ languages
Longest file2 hours or 100 MB per request, 24 hours as a job300 minutes per file
APIOpenAI-compatibleSoniox’s own

Price with speaker labels

Audio a monthAvenceraSoniox Async
10 hours$0.70$1.00 1.4×
100 hours$7.00$10.00 1.4×
1,000 hours$70.00$100.00 1.4×
10,000 hours$700.00$1,000.00 1.4×

See every provider at any volume on the pricing page.

Accuracy

Speaker labels

Avencera’s speaker labels make fewer errors than Soniox Async v5 on all 10 recording types in pyannoteAI’s benchmark. Averaged across them, the diarization error rate is 23.5% for Avencera and 36.6% for Async v5.

Diarization error rate by recording type, lower is better
  1. Radio interviews 12 recordings, 3 or 4 speakers

    Avencera by 17.5 points

    Avencera community-1: 10.4%. Soniox Async v5: 27.9%.

  2. Clinical interviews 51 recordings, 2 or 3 speakers

    Avencera by 5.0 points

    Avencera community-1: 23.5%. Soniox Async v5: 28.5%.

  3. Courtroom 12 recordings, 3 to 9 speakers

    Avencera by 24.3 points

    Avencera community-1: 11.6%. Soniox Async v5: 35.9%.

  4. Phone calls 61 recordings, 2 speakers

    Avencera by 13.1 points

    Avencera community-1: 12.2%. Soniox Async v5: 25.3%.

  5. Task dialogues 19 recordings, 2 speakers

    Avencera by 12.4 points

    Avencera community-1: 10.1%. Soniox Async v5: 22.5%.

  6. Meetings 11 recordings, 3 to 6 speakers

    Avencera by 20.0 points

    Avencera community-1: 36.4%. Soniox Async v5: 56.4%.

  7. Restaurant conversations 12 recordings, 4 to 8 speakers

    Avencera by 11.6 points

    Avencera community-1: 51.0%. Soniox Async v5: 62.6%.

  8. Field interviews 22 recordings, 2 or 3 speakers

    Avencera by 8.8 points

    Avencera community-1: 18.2%. Soniox Async v5: 27.0%.

  9. Lab interviews 12 recordings, 2 speakers

    Avencera by 8.6 points

    Avencera community-1: 14.1%. Soniox Async v5: 22.7%.

  10. Web video 35 recordings, 1 to 7 speakers

    Avencera by 9.5 points

    Avencera community-1: 47.8%. Soniox Async v5: 57.3%.

Words

Soniox transcribes words more accurately on the one published test that covers both, by up to 0.7 points.

Word error rate by benchmark, lower is better
  1. Artificial Analysis Word error rate, measured on each provider’s own API

    Async v5 by 0.7 points

    Avencera Parakeet v3: 4.5%. Soniox Async v5: 3.8%.

Which to choose

Choose Soniox if

  • Word accuracy matters most. Async v5 scores 3.8% on the Artificial Analysis, against 4.5% for Parakeet v3.
  • You need real-time streaming. Soniox offers it; Avencera transcribes recorded audio only.
  • You need more languages. Soniox lists 60+ languages.
  • You need an API today. Avencera opens soon.

Choose Avencera if

  • You want the lower bill. Soniox Async costs 1.4× as much at 100 hours a month with speaker labels.
  • You want better speaker labels for less. In pyannoteAI’s benchmark, Avencera’s speaker labels make fewer errors than Async v5 on all 10 recording types, 23.5% against 36.6% on average.
  • You want prepaid credit with no subscription, no minimum and no expiry.
  • You want a fixed price per hour of audio. Soniox bills by tokens, so the cost of an hour depends on how much is said in it.
  • 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 Soniox?
Yes. Avencera transcribes from $0.06 an hour, or $0.07 with speaker labels. At 100 hours a month with speaker labels, Soniox Async costs $10.00 against $7.00 at Avencera, 1.4× as much.
Is Avencera more accurate than Soniox?
Avencera’s speaker labels make fewer errors than Soniox Async v5 on all 10 recording types in pyannoteAI’s benchmark. Averaged across them, the diarization error rate is 23.5% for Avencera and 36.6% for Async v5. Soniox transcribes words more accurately on the one published test that covers both, by up to 0.7 points. Async v5 scores 3.8% on the Artificial Analysis, against 4.5% for Parakeet v3.
Is Soniox cheaper than Avencera?
Close, but no. Soniox’s token billing comes to about the hourly price shown here for typical speech, a little above Avencera’s cheapest speaker transcript.
How do I switch from Soniox to Avencera?
Avencera uses OpenAI’s transcription API format, so any OpenAI SDK works. Send the same audio files you send Soniox, and map its response fields to the OpenAI-style transcript.

Sources

Multiples in brackets compare with Avencera’s cheapest offer at the same volume.

Monthly list prices for recorded audio with speaker labels, before free credit, discounts or contracts. Each plan uses whichever of its options costs least at that volume.

Accuracy: Lower is better, and results within 0.1 points count as level. pyannoteAI ran its diarization benchmark itself, without telling any system how many speakers to expect. Avencera’s speaker labels run community-1 through speakrs, which matches pyannote’s published error rates. Averages weight each recording type equally. Artificial Analysis tests Parakeet v3 as hosted by Together AI.

Vendor prices and features from each vendor’s own pages, checked October 23, 2026. Benchmark results as of October 23, 2026 for the Artificial Analysis speech-to-text and October 22, 2026 for the pyannoteAI diarization benchmark.