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vvsotnikov/Qwen3.8-27B-MLX-4bit
Qwen3.8-27B-MLX-4bit is a image-text-to-text model from vvsotnikov. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as apache-2.0.
This model was converted to MLX format from Qwen/Qwen3.8-27B using mlx-vlm version 0.6.8, and quantized to 4 bits, so it runs on Apple silicon through mlx-vlm. Refer to the original model card for more details on the…
Downloads · 30 days
107
13% of all-time downloads
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From the Hugging Face model README
This model was converted to MLX format from
Qwen/Qwen3.8-27B using mlx-vlm version
0.6.8, and quantized to 4 bits, so it runs on Apple
silicon through mlx-vlm. Refer to the
original model card for more details
on the model itself.
Pair it with
Qwen3.8-27B-MTP-MLX-4bit
to get speculative decoding, because Qwen carries a Multi-Token Prediction
head that the MLX conversion moves into a separate repository.
pip install -U mlx-vlm
mlx_vlm generate \
--model vvsotnikov/Qwen3.8-27B-MLX-4bit \
--draft-model vvsotnikov/Qwen3.8-27B-MTP-MLX-4bit \
--prompt "Write a quicksort in Python." \
--max-tokens 256 --temperature 0.6 --enable-thinking
Drop --draft-model to decode without the speculator.
mlx_vlm convert --hf-path Qwen/Qwen3.8-27B \
--mlx-path Qwen3.8-27B-MLX-4bit -q --q-bits 4 --q-group-size 64
The quantization is uniform affine at 4 bits with group size
64, and it covers 498 modules
of the language model including embed_tokens, lm_head and the
linear_attn projections. The vision tower stays dense in bfloat16, since
the converter skips multimodal modules by default.
Every artifact in this release passed an automated check before it was published, and nothing became public until its remote checksums matched the local build.
| Check | Result |
|---|---|
| Quantization | {bits: 4, group_size: 64, mode: affine} |
| Quantized modules | 498 of 2180 tensors |
| Vision tower | dense, 333 tensors |
| MTP tensors | 0, moved to the drafter repository |
| Acceptance with the 4-bit drafter | 93.5% of drafted tokens accepted, 2.86 accepted tokens/round, over 70 rounds, 15.982 tok/s |
The weights derive from Qwen/Qwen3.8-27B
under Apache 2.0, so the original license and its terms carry over.
Read the license itself before you use this model,
and refer to the upstream model card for the model's capabilities and limits.