MTP settings boost MoE model performance on local hardware

A user on r/LocalLLaMA has shared their findings on optimizing Multi Token Prediction (MTP) settings for Mixture of Experts (MoE) models, particularly Gemma4-26B-A4B-IT-QAT. Contrary to previous consensus, the user found that adjusting MTP parameters like n-max and min-p significantly boosted performance on their hardware, achieving an increase from 88 tokens/sec to 132 tokens/sec for natural language tasks. The optimal settings varied between models and task types, with programming tasks preferring different parameters than general language tasks. AI

IMPACT Optimizing MTP settings can lead to significant performance gains for users running MoE models locally.

RANK_REASON User-generated findings on optimizing model parameters for local hardware, not a formal release or research paper.

Read on r/LocalLLaMA →

• Gemma4-26B-A4B-IT-QAT
• llama.cpp
• Multi Token Prediction
• RTX 5060 Ti

• infra
• model release

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