ARK-ASR-0.6B-onnx

ARK-ASR-0.6B ONNX

ONNX export of Audio8/ARK-ASR-0.6B for onnx-asr. All credit for the model goes to Audio8 (AutoArk AI). This repository only contains the converted graphs; the weights are the original ones.

The model is a speech-LLM: a Whisper-large-v3-style audio encoder with rotary position embeddings, an MLP adapter that merges four encoder frames into one embedding, and a Qwen2 0.6B causal language model that writes the transcription.

Usage

pip install onnx-asr[cpu,hub]

import onnx_asr

model = onnx_asr.load_model("speech-llm", "OpenVoiceOS/ARK-ASR-0.6B-onnx")
print(model.recognize("audio.wav"))

# int8 weights
model = onnx_asr.load_model("speech-llm", "OpenVoiceOS/ARK-ASR-0.6B-onnx", quantization="int8")

Files

Graph contract

Accuracy

Four FLEURS clips (2 English, 2 Mandarin), greedy decoding, compared against the PyTorch model in float32:

• fp32 ONNX: 4 of 4 transcriptions identical to PyTorch, character for character.
• int8 ONNX: 3 of 4 identical. One Mandarin clip stops early and loses the last clause.

Speed on a 12-core CPU under load: RTF 0.35 to 0.61 (fp32) and 0.09 to 0.29 (int8).

Licence

Apache 2.0, the same licence as the source model. The model was published by Audio8; see the source repository and the paper arXiv:2605.28139.