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ThinkingCap for Gemma-4-26B-A4B

BottleCap AI post-trained Google's sparse MoE (26B total, ~4B active) to reach answers witBottleCap AI 对 Google 的稀疏 MoE 模型（总参数 26B、每个 token 约 4B 激活）做后训练，让它用更少的推理 token 得出答案：12 个基准上
BottleCap AI 对 Google 的稀疏 MoE 模型（总参数 26B、每个 token 约 4B 激活）做后训练，让它用更少的推理 token 得出答案：12 个基准上BottleCap AI post-trained Google's sparse MoE (26B total, ~4B active) to reach answers wit
Global3First seen 2026-10-24
bottlecapai.com/post/thinkingcap-gemma-4-26b/ ↗

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Timeline · 1

  1. Launch
    ThinkingCap for Gemma-4-26B-A4B: 39% less thinking on average, same accuracy: BottleCap AI post-trained Google's sparse MoE (26B total, ~4B…ThinkingCap 版 Gemma-4-26B-A4B：平均少想 39%，准确率不变：BottleCap AI 对 Google 的稀疏 MoE 模型（总参数 26B、每个 token 约 4B 激活）做后训练，让它用更少的推理 token 得出答案：12 个基准上思考量平均…