> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pyannote.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Models

> Choose the right speaker diarization model for your audio processing needs

<CardGroup>
  <Card title="Precision-2" icon="star">
    Our state-of-the-art Premium model delivering the most accuracy for teams and enterprises with support for
    voiceprints and speaker identification. 28% more accurate than Community-1.
  </Card>

  <Card title="Community-1" icon="users">
    Our latest open-source model. Useful for local development and research. Also available as a hosted option for teams
    who want to avoid infrastructure management.
  </Card>
</CardGroup>

## Choosing the right model

### 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.

<Tip>Self-hosted options for Precision-2 are available on Enterprise plans.</Tip>

**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 <Icon icon="arrow-up-right" iconType="solid" />](https://www.pyannote.ai/blog/precision-2)

***

### 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 <Icon icon="arrow-up-right" iconType="solid" />](https://www.pyannote.ai/blog/community-1)

***

### 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 <Icon icon="arrow-up-right" iconType="solid" />](https://github.com/pyannote/pyannote-audio)

***

## How to specify a model in diarization requests

When making a diarization request, you can specify which model to use using the `model` parameter:

```bash theme={null}
curl -X POST "https://api.pyannote.ai/v1/diarize" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://files.pyannote.ai/marklex1min.wav",
    "model": "precision-2"
  }'
```

By default, if you do not specify a model, the API will use the Precision-2 model.

### 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>
  **Note:** Speaker identification and voiceprint features are not available for Community-1 models. These advanced
  features are exclusive to Precision-2
</Note>

### 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

## Pricing

For detailed pricing information, visit our [pricing page](https://www.pyannote.ai/pricing).