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Overview

Sortformer is NVIDIA’s end-to-end streaming speaker diarization model, converted to CoreML. Unlike the pyannote pipeline (segmentation + clustering), Sortformer is a single neural network with 4 fixed speaker slots. Model: FluidInference/diar-streaming-sortformer-coreml

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Key Properties

  • 4 fixed speaker slots with real-time inference
  • No separate segmentation + clustering stages
  • Streaming only (no offline mode)
  • Best for scenarios with 4 or fewer speakers

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When to Use Sortformer vs Pyannote

Sortformer can beat pyannote on benchmarks with certain configs, but benchmark DER does not always reflect production performance. In practice:
Benchmarks are not always consistent with production usage. Pyannote’s offline pipeline with aggressive tuning can score lower DER on AMI, but those configs may not generalize. Sortformer’s 32% DER is more representative of real-world performance on meetings with 4 or fewer speakers.

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Benchmarks

AMI SDM (16 meetings, single distant microphone). Audio length: 30.4s chunks (NVIDIA high-latency config): See full benchmarks for per-meeting breakdown.

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CLI