Applying Logit Penalties to Qwen-3.5-4B Improves MATH-500 Performance
September 27, 2026
Applying negative logit biases to hedging tokens like wait, maybe, and perhaps increases accuracy on MATH-500 benchmarks for Qwen-3.5-4B GGUF quantizations. This technique reduces uncertainty-driven stalling in reasoning tasks using llama.cpp parameters.
HOW THIS AFFECTS YOU
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builderYou can improve reasoning accuracy in local deployments by adjusting logit biases for specific tokens.
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researcherThis demonstrates how simple steering via logit penalties can mitigate hedging behavior in small reasoning models.