Researchers at Hugging Face developed a method to compress reasoning tokens without sacrificing model performance. This approach optimizes how models handle internal "thought" processes before delivering a final answer. It reduces latency and compute costs for developers deploying reasoning-heavy models. The result is a leaner inference pipeline for complex tasks.