Prague lab BottleCapAI releases ThinkingCap models cutting thinking tokens up to 69% with negligible accuracy loss
JFPuget · x · 2026-10-27
BottleCapAI, a Prague-based AI lab, argues frontier models drastically overthink and burn tokens unnecessarily. It fine-tunes existing open models to think less while staying accurate, and last week released three ThinkingCap models:
- NVIDIA Nemotron: up to 31% less thinking (23% on average) with comparable benchmark accuracy
- Alibaba Qwen3.8-Flash-Next: 39% fewer thinking tokens on average for 1 point of accuracy loss
- Google Gemma 4 (Gemma-4-26B-A4B): first ThinkingCap on a Google model — up to 69% fewer thinking tokens (38.9% average) for just 0.15pp accuracy loss; the enterprise ThinkingCap PRO cuts up to 87.6% (62% average)
Weights are on Hugging Face with GGUF builds and a blogpost. The payoff: lower token spend and reduced hardware requirements.
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