license: apache-2.0
pipeline_tag: automatic-speech-recognition
base_model: Qwen/Qwen3-ASR-0.6B
tags:
- executorch
library_name: executorch
qwen-3-asr
This repository hosts Qwen3-ASR exported for the
React Native ExecuTorch
library as ExecuTorch .pte programs, ready to run on device.
Variants
| Path | Backend | Precision | Audio per pass |
|---|---|---|---|
0_6b/xnnpack/qwen3_asr_0_6b_xnnpack_8da4w.pte |
xnnpack | 8da4w | 30 s |
0_6b/mlx/qwen3_asr_0_6b_coreml_mlx_4w.pte |
Core ML (audio tower) + MLX | fp16 tower, 4w decoder | 30 s |
Decoder linears are 8da4w (group 32) except decoder layers 0–1, which stay at 8da8w; the audio tower is 8da8w with an int8 conv stem. WER on the first 100 LibriSpeech test-clean clips: 2.46% (fp32: 2.14%).
The Core ML + MLX file runs the audio tower on Core ML in fp16 and the decoder on MLX with 4-bit weights (group 32, layers 0–1 at 8 bits): WER 2.51%. It needs both backends in the runtime.
Repository structure
0_6b/tokenizer.json 10.9 MiB
0_6b/xnnpack/config.json
0_6b/mlx/config.json
0_6b/mlx/qwen3_asr_0_6b_coreml_mlx_4w.pte 771 MiB
0_6b/xnnpack/qwen3_asr_0_6b_xnnpack_8da4w.pte 675 MiB
Compatibility
These files are published for the ExecuTorch v1.4.1 runtime. ExecuTorch gives no forward compatibility guarantee, so an older runtime may fail to load them.
To use them in React Native ExecuTorch, pass the model constant shipped in the library's model registry to the corresponding task pipeline. See the documentation.
To load these files in your own ExecuTorch runtime, read the compatibility note first.