This repository contains the Multi-Token Prediction (MTP) drafter weights split from Qwen/Qwen3.8-27B and quantized with mlx_vlm.convert for mlx-vlm speculative decoding.
This is not a standalone model. Use it as the draft model alongside a compatible Qwen3.8 27B target checkpoint.
mlx_vlm generate \
--model mlx-community/Qwen3.8-27B-8bit \
--draft-model mlx-community/Qwen3.8-27B-MTP-8bit \
--prompt "Write a quicksort in Python." \
--max-tokens 256 \
--enable-thinking
--draft-kind mtp is detected automatically from model_type.
qwen3_5_mtpmlx-vlm1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0The adapter holds only the MTP drafter weights; the target supplies the token embeddings and language-model head at runtime. Use an adapter and target derived from the same Qwen3.8 27B checkpoint. The upstream Apache 2.0 license and model limitations continue to apply.
This repository contains the Multi-Token Prediction (MTP) drafter weights split from Qwen/Qwen3.8-27B and quantized with mlx_vlm.convert for mlx-vlm speculative decoding.
This is not a standalone model. Use it as the draft model alongside a compatible Qwen3.8 27B target checkpoint.
mlx_vlm generate \
--model mlx-community/Qwen3.8-27B-8bit \
--draft-model mlx-community/Qwen3.8-27B-MTP-8bit \
--prompt "Write a quicksort in Python." \
--max-tokens 256 \
--enable-thinking
--draft-kind mtp is detected automatically from model_type.
qwen3_5_mtpmlx-vlm1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0The adapter holds only the MTP drafter weights; the target supplies the token embeddings and language-model head at runtime. Use an adapter and target derived from the same Qwen3.8 27B checkpoint. The upstream Apache 2.0 license and model limitations continue to apply.