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Precision-2

Highest-accuracy diarization for recordings, with support for voiceprints and speaker identification.

Live-1

Streaming diarization over WebSocket for live audio.

Community-1

Open-source diarization for research, prototyping, and self-hosting.

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Choosing the right model

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Precision-2

Best for: Startups, SMEs, and enterprises who need the state-of-the-art in speaker diarization accuracy and advanced features like voiceprints and speaker identification. Precision-2 is 28% more accurate, on average, than Community-1.
Self-hosted options for Precision-2 are available on Enterprise plans.
Typical use cases: phone call analytics, meeting transcription with speaker attribution, video dubbing and timestamp-critical workflows, building training data for voice assistants, and more. Advanced features:
  • Speaker identification with voiceprints: Identify known speakers in your audio using pre-enrolled voiceprints
  • Exclusive diarization mode: Returns speaker diarization where only one single speaker (the most likely to be transcribed) is active at a time, making STT reconciliation easier
  • Flexible speaker count control: Set minSpeakers, maxSpeakers and numSpeakers parameters for any number of speakers
  • Human-in-the-loop correction: Use confidence scores to help streamline manual correction processes
Learn more about Precision-2

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Live-1

Best for: Teams building live voice products that need speaker labels before a recording finishes: contact centers, meeting tools, broadcast workflows, and real-time voice agents. Typical use cases: live meeting assistants, contact center agent assist, live captioning with speaker attribution, broadcast speaker attribution, and multi-party voice agents that need to track who is speaking. Advanced features:
  • Sub-300ms latency: Speaker labels arrive fast enough for live captioning and real-time agent assist, tested against noisy, real-world audio rather than clean studio recordings.
  • Native streaming architecture: Processes audio in 100ms chunks over WebSocket, with a speaker tracking layer that holds consistency across the stream without needing the full conversation.
  • Built for real conditions: Trained and validated on overlapping speech, background noise, and conversations with more than two participants.
Technical specs:
  • Up to 8 speakers, up to 5 hours duration per stream
  • Input: 16 kHz mono audio, 100ms chunks over WebSocket
  • Output: diarization_speaker_start and diarization_speaker_end events, each with a start or end timestamp and speaker label
Learn more about Live-1

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Community-1 (hosted)

Best for: Teams who want the open-source model without managing infrastructure Typical use cases: Prototyping, low-volume production workloads, testing and validation Key Benefits:
  • Cost efficiency: hosted at cost, ideal for experimentation and low-volume workloads
  • No infrastructure management: Focus on your application while we handle the deployment
  • Easy migration: Start with hosted Community-1 and upgrade to Precision-2 when needed
  • Same powerful model: Access the same Community-1 model through our API without setup complexity
Learn more about Community-1

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Community-1 (self-hosted with pyannote.audio 4.0)

Best for: Researchers, developers, and personal hobby projects who want full control over their diarization models and workflows. Typical use cases: Academic work, product-iteration, prototyping, and custom diarization deployment (e.g., dataset-specific fine-tuning or custom reconciliation with STT). Key Benefits:
  • Best open-source speaker diarization model available - outperforms pyannote.audio 3.1 across all key metrics
  • Open-source flexibility: Full transparency into model weights and code allowing local and offline training and inference.
Trade-offs:
  • Lower accuracy compared to Precision-2
  • No support for advanced features like speaker identification and voiceprints
  • Requires deploying the model on your own infrastructure
Learn more about pyannote.audio 4.0

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How to specify a model in diarization requests

When making a diarization request, you can specify which model to use using the model parameter:
By default, if you do not specify a model, the API will use the Precision-2 model.

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Switch between models

You can easily switch between models by changing the model parameter:
  • "model": "community-1" for Community-1
  • "model": "precision-2" for Precision-2
Note: Speaker identification and voiceprint features are not available for Community-1 models. These advanced features are exclusive to Precision-2

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Compare results between models

To compare performance between models on your specific data:
  1. Process the same audio file with both models
  2. Compare the diarization results
  3. Evaluate which model provides better accuracy for your use case

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Pricing

For detailed pricing information, visit our pricing page.