Optimized Gemma-4-26B Cuts Thinking Tokens by Up to 69%

1 reports archived1 independent sourcesupdated 10/23/2026, 22:43:02

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Bottlecap AI released an optimized version of Google's Gemma-4-26B-A4B, reducing average Chain-of-Thought (CoT) token usage by ~39% (up to 69%) with only a 0.15% accuracy drop. This drop-in replacement significantly lowers inference costs and minimizes repetitive looping, demonstrating effective post-processing or fine-tuning strategies for optimizing long reasoning chains.

LATEST/Bottlecap AI released an optimized version of Google's Gemma-4-26B-A4B, reducing average Chain-of-Thought (CoT) token usage by ~39% (up to 69%) with only a 0.15% accuracy drop. This drop-in replacement significantly lowers inference costs and minimizes repetitive looping, demonstrating effective post-processing or fine-tuning strategies for optimizing long reasoning chains.

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Hacker News AIT2·Oct 23, 22:4368 pts
Optimized Gemma-4-26B Cuts Thinking Tokens by Up to 69%
- Optimized Gemma-4-26B reduces thinking tokens by 38.9% on average with only 0.15pp accuracy loss
- Repetitive looping rate drops from 3.6% in the original model to 0.8%
- Compatible with vLLM serving stack as a drop-in replacement
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