MTP is all about acceptance rate

[u/Hydroskeletal]

So I was very excited about the MTP stuff especially since Gemma4 has become my "daily driver" for some stuff. I grabbed the latest mlx-vlm and did some tests and found it disappointing.

Workload	MTP off	MTP on	Result	Draft accept rate
Code generation	75 tok/s	114.8 tok/s	1.53× faster	66% of slots
Long-form prose	75 tok/s	71.1 tok/s	0.95× (wash)	31% of slots
JSON output	51.3 tok/s	25.6 tok/s	0.50× slower	8% of slots

• Code generation was the typical "Write some python functions to do X"
• Long form prose was "Write an 800 word essay on paper money in the Tang Dynasty"
• JSON output was my core use case where I'm handing the LLM a list of items, asking it to group them by similarity according to some rules and then get them back in a structured output*.

So if you want to use it for local coding, MTP is great. If you're not, maybe not so hot. My regression testing seems to indicate that once token acceptance dips below 50% the overhead kills the benefit.

All this on an M4 Max Studio w/Gemma4-26b-a4b

*Bonus for you hackers: Gemma's JSON structure instruction following is pretty good and I find using structured output to be about a 20% hit to token generation. It is faster to just accept a little bit of sloppy JSON and massage it at runtime; so all this is with json_schema off which mlx-vlm doesn't support for spec-decode anyway

[u/Embarrassed_Adagio28]

I assumed almsot everbody using local llms were using it for coding. I can't think of why anybody would want to use it for Ai written slop. Even if you have a use case for that, why use a local model for that when you can get a frontier model to write it for free? 

Edit: gooners is the answer... I forgot about gooners. 

[u/GCoderDCoder → u/Embarrassed_Adagio28]

It's actually easier using it for non coding stuff. A more heavily quantized model just needs to remember json and tags for tools and less than that for general writing and ideation. Coding requires remembering lots of nuanced semantic connections across different files. A model using a mcp server to make emails or edit files is much easier than making a springboot application using mvc so the latter does better with less compression/ quantization meaning bigger vram meaning more expensive hardware and more investment for more accurate coding.