Instructions to use majentik/Qwen3-ASR-0.6B-MLX-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use majentik/Qwen3-ASR-0.6B-MLX-8bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Qwen3-ASR-0.6B-MLX-8bit majentik/Qwen3-ASR-0.6B-MLX-8bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Provenance — majentik/Qwen3-ASR-0.6B-MLX-8bit
- Upstream repo:
Qwen/Qwen3-ASR-0.6B-hf - Upstream revision:
6aa69c382e2b426eee1f5870d4c95859a74b6445 - Quantization: bits=8, mode=affine, group_size=64
- Command:
python -m pipelines.mlx_direct_quantize --model qwen3-asr-0.6b --base-dir /private/tmp/mlx-direct-release/qwen3-asr-0.6b/base --out-dir /tmp/mlx-direct-release/qwen3-asr-0.6b/8bit --bits 8 --mode affine --group-size 64 - Input bytes (BF16 base): 1576380161
- Output bytes (this variant): 1017761038
- Toolchain: mlx 0.31.2, huggingface_hub 0.36.2
- Generated: 2026-07-03T14:27:03.678461+00:00
Audio-inference smoke was performed post-upload on 2026-07-03; this variant passed its CER gate — see the README's Audio inference smoke section. General runtime support remains pending upstream mlx-lm support for the qwen3_asr audio-text architecture (the Hugging Face runtime requires transformers 5.13+ — qwen3_asr merged after the 5.12.1 release).