A user on Reddit's r/LocalLLaMA forum investigated how model quantization affects the draft rate in Multi Token Prediction (MTP) for large language models. The tests used Gemma 4-31B-it as the main model, with various quantization levels (Q5_K_S down to IQ2_M), and Gemma 4-31B-it-assistant as the MTP drafter. Results showed that acceptance rates decrease as draft depth increases across all quantization levels, with lower bit-rate models exhibiting slightly reduced consistency with the drafter. AI
IMPACT Quantization levels can affect the efficiency of speculative decoding techniques in LLMs.
RANK_REASON User-conducted research on LLM performance characteristics. [lever_c_demoted from research: ic=1 ai=1.0]
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