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ToPo-ToPo/Qwen3.8-27B-MTP-4bit
Qwen3.8-27B-MTP-4bit is a machine learning model from ToPo-ToPo. Use it for the machine learning 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.
MTP (multi-token prediction) drafter for speculative decoding with Qwen/Qwen3.8-27B on Apple Silicon (mlx-vlm).
Downloads · 30 days
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From the Hugging Face model README
MTP (multi-token prediction) drafter for speculative decoding with
Qwen/Qwen3.8-27B on Apple Silicon (mlx-vlm).
This is not a standalone chat model — it only works bound to a Qwen3.8-27B target model.
mtp.* weights (15 tensors, isolated in
model-00018-of-00018.safetensors) with mlx-vlm 0.6.9:
python -m mlx_vlm.speculative.drafters.qwen3_5_mtp.split --model Qwen/Qwen3.8-27B --output .block_size: 3, model_type: qwen3_5_mtpGains are largest on structured output (code, JSON tool calls) and smallest on free-form prose. Stable over 589 rounds with rejections — no rollback crash.
The bf16 and 4bit drafters accept identically under greedy decoding (quantization rarely flips the argmax); bf16 was marginally better on code, 4bit uses less memory.
Measure it yourself. Speedup depends on hardware, target quantization, workload and the
mlx-vlm version — on the machine used here the reference pair
Qwen3.6-27B-4bit + mlx-community/Qwen3.6-27B-MTP-4bit showed no speedup at all, so any
number quoted elsewhere may not transfer to your setup.
mlx_vlm.generate --model ToPo-ToPo/Qwen3.8-27B-mlx-4bit \
--draft-model ToPo-ToPo/Qwen3.8-27B-MTP-4bit --draft-kind mtp \
--prompt "..." --max-tokens 400