ModelVerifiedExternal

Parakeet Realtime Eou 120m Coreml

nvidia-open-model-license

Sourcehuggingface.co/aoiandroid/parakeet-realtime-eou-120m-coreml/tree/1b8ea0eb7770cd61046070cc7500ea4901e16541

KindOtherBase modelnvidia/parakeet_realtime_eou_120m-v1VersionRevision 1b8ea0ePublisher@aoiandroidCgrade

Model source

Kind: Other
File size: 243 B–203 MB
Base model: nvidia/parakeet_realtime_eou_120m-v1
Version: vRevision 1b8ea0e
Updated: Oct 5, 2026
Publisher: @aoiandroid
Downloads: 11
Parameters: 120M
Source: Hugging Face

Source description

Parakeet Realtime EOU 120M — CoreML

CoreML conversion of [nvidia/parakeet-realtime-eou-120m-v1](https://huggingface.co/nvidia/parakee t-realtime-eou-120m-v1) for streaming speech recognition with end-of-utterance detection on Apple Silicon.

Used by FluidAudio for real-time transcription.

Models

The RNNT pipeline is split into three CoreML models, exported at two chunk sizes:

Model	Description
`streaming_encoder.mlmodelc`	FastConformer encoder with loopback state caching
`decoder.mlmodelc`	1-layer LSTM decoder (640 hidden units)
`joint_decision.mlmodelc`	Joint network for token prediction + EOU detection

Chunk Size Variants

Variant	Latency	WER (test-clean)	RTFx (M2)
`160ms/`	160ms	8.29%	4.78x
`320ms/`	320ms	4.87%	12.48x

Benchmarked on LibriSpeech test-clean (2620 files, 5.40h audio) on Apple M2.

Usage with FluidAudio

import FluidAudio

let manager = StreamingEouAsrManager()
await manager.initialize()

// Transcribe with EOU detection
await manager.startStreaming(
    eouCallback: { transcript in
        print("Utterance complete: \(transcript)")
    },
    partialCallback: { partial in
        print("Partial: \(partial)")
    }
)

// Feed audio chunks as they arrive
await manager.feedAudio(samples)

CLI

Transcribe a file

swift run fluidaudio parakeet-eou --input audio.wav

Benchmark

swift run -c release fluidaudio parakeet-eou --benchmark --chunk-size 320

Architecture

120M parameter RNNT (Recurrent Neural Network Transducer) with:

Encoder: 17-layer FastConformer with cache-aware streaming
Decoder: 1-layer LSTM, 640 hidden size
Joint: Linear projection with 1027 output classes (1024 tokens + EOU token + SOS + blank)
EOU token: ID 1024 signals end-of-utterance

Streaming State

The encoder maintains loopback state between chunks: ┌─────────────────────┬──────────────────┬───────────────────────┐ │ State │ Shape │ Description │ ├─────────────────────┼──────────────────┼───────────────────────┤ │ preCache │ [1, 128, N] │ Mel-level context │ ├─────────────────────┼──────────────────┼───────────────────────┤ │ cacheLastChannel │ [17, 1, 70, 512] │ Conformer layer cache │ ├─────────────────────┼──────────────────┼───────────────────────┤ │ cacheLastTime │ [17, 1, 512, 8] │ Temporal cache │ ├─────────────────────┼──────────────────┼───────────────────────┤ │ cacheLastChannelLen │ [1] │ Cache length tracking │ └─────────────────────┴──────────────────┴───────────────────────┘ Export

Converted from PyTorch using coremltools. To re-export:

python3 Scripts/ParakeetEOU/Conversion/convert_split_encoder.py
--output-dir Models/ParakeetEOU
--model-id nvidia/parakeet-realtime-eou-120m-v1

License

NVIDIA Open Model License — see https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/.

Original model: https://huggingface.co/nvidia/parakeet-realtime-eou-120m-v1

Sources

1 source

Hugging FacePrimaryVersion 1b8ea0eb7770cd61046070cc7500ea4901e16541

huggingface.co/aoiandroid/parakeet-realtime-eou-120m-coreml/tree/1b8ea0eb7770cd61046070cc7500ea4901e16541

Verified Aug 19

Model artifacts

41 artifacts

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1280ms/decoder.mlmodelc/weights/weight.bin

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1280ms/joint_decision.mlmodelc/coremldata.bin

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160ms/decoder.mlmodelc/coremldata.bin

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160ms/decoder.mlmodelc/weights/weight.bin

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160ms/decoder.mlpackage/Data/com.apple.CoreML/weights/weight.bin

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160ms/joint_decision.mlmodelc/analytics/coremldata.bin

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160ms/joint_decision.mlmodelc/coremldata.bin

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160ms/joint_decision.mlmodelc/weights/weight.bin

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160ms/parakeet_eou_preprocessor.mlmodelc/analytics/coremldata.bin

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160ms/parakeet_eou_preprocessor.mlmodelc/coremldata.bin

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160ms/parakeet_eou_preprocessor.mlpackage/Data/com.apple.CoreML/weights/weight.bin

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160ms/streaming_encoder.mlmodelc/analytics/coremldata.bin

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160ms/streaming_encoder.mlpackage/Data/com.apple.CoreML/weights/weight.bin

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320ms/decoder.mlmodelc/analytics/coremldata.bin

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320ms/decoder.mlmodelc/coremldata.bin

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320ms/decoder.mlmodelc/weights/weight.bin

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320ms/decoder.mlpackage/Data/com.apple.CoreML/weights/weight.bin

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320ms/joint_decision.mlmodelc/analytics/coremldata.bin

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320ms/joint_decision.mlmodelc/coremldata.bin

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320ms/joint_decision.mlmodelc/weights/weight.bin

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320ms/joint_decision.mlpackage/Data/com.apple.CoreML/weights/weight.bin

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320ms/streaming_encoder.mlmodelc/analytics/coremldata.bin

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320ms/streaming_encoder.mlmodelc/weights/weight.bin

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Source excerpts

3 excerpts

ReadmeJul 11huggingface.co/aoiandroid/parakeet-realtime-eou-120m-coreml

--- license: other license_name: nvidia-open-model-license license_link: >- https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/ language: - en metrics: - wer library_name: nemo tags: - speech-recognition - FastConformer - end-of-utterance - voice agent pipeline_tag: automatic-speech-recognition base_model: - nvidia/parakeet_realtime_eou_120m-v1 base_model_relation: finetune --- # Parakeet Realtime EOU 120M — CoreML CoreML conversion of [nvidia/parakeet-realtime-eou-120m-v1](https://huggingface.co/nvidia/parakee t-realtime-eou-120m-v1) for streaming speech recognition with end-of-utterance detection on Apple Silicon. Used by [FluidAudio](https://github.com/FluidInference/FluidAudio) for real-time transcription. ## Models The RNNT pipeline is split into three CoreML models, exported at two chunk sizes: | Model | Description | |-------|-------------| | `streaming_encoder.mlmodelc` | FastConformer encoder with loopback state caching | | `decoder.mlmodelc` | 1-layer LSTM decoder (640 hidden units) | | `joint_decision.mlmodelc` | Joint network for token prediction + EOU detection | ### Chunk Size Variants | Variant | Latency | WER (test-clean) | RTFx (M2) | |---------|---------|-------------------|------------| | `160ms/` | 160ms | 8.29% | 4.78x | | `320ms/` | 320ms | 4.87% | 12.48x | Benchmarked on LibriSpeech test-clean (2620 files, 5.40h audio) on Apple M2. ## Usage with FluidAudio ```swift import FluidAudio let manager = StreamingEouAsrManager() await manager.initialize() // Transcribe with EOU detection await manager.startStreaming( eouCallback: { transcript in print("Utterance complete: \(transcript)") }, partialCallback: { partial in print("Partial: \(partial)") } ) // Feed audio chunks as they arrive await manager.feedAudio(samples) ``` CLI # Transcribe a file swift run fluidaudio parakeet-eou --input audio.wav # Benchmark swift run -c release fluidaudio parakeet-eou --benchmark --chunk-size 320 Architecture 120M parameter RNNT (Recurrent Neural Network Transducer) with: - Encoder: 17-layer FastConformer with cache-aware streaming - Decoder: 1-layer LSTM, 640 hidden size - Joint: Linear projection with 1027 output classes (1024 tokens + EOU token + SOS + blank) - EOU token: ID 1024 signals end-of-utterance Streaming State The encoder maintains loopback state between chunks: ┌───────────────...

NoteAug 19huggingface.co/aoiandroid/parakeet-realtime-eou-120m-coreml

Source context: 11 downloads · 0 likes · Pipeline automatic-speech-recognition · Library nemo · Repo aoiandroid/parakeet-realtime-eou-120m-coreml

NoteJul 17huggingface.co/aoiandroid/parakeet-realtime-eou-120m-coreml

Source context: 24 downloads · 0 likes · Pipeline automatic-speech-recognition · Library nemo · Repo aoiandroid/parakeet-realtime-eou-120m-coreml