←Back to NewsAI News/LlmsmodelLlmsPost TrainingUkisAI's Swift-Qwen3.8 Slashes AI Reasoning Tokens by 58% With Almost No Accuracy LossUkisAI's Swift-Qwen3.8-27B cuts thinking tokens by 58% while keeping accuracy within 1% of the base, delivering roughly 2x faster reasoning.SourceAlphaSignalPublishedSep 8, 2026, 1:35 PMAuthorAlphaSignal NewsroomRead1 min readUkisAI's Swift-Qwen3.8-27B cuts thinking tokens by 58% while keeping accuracy within 1% of the base, delivering roughly 2x faster reasoning.Reporting is indexed from AlphaSignal. Rights remain with the original publisher and cited sources.Read original report ↗Next readsMultiverse Computing · newsMultiverse Computing's Quasar 1.1 Uses Quantum Data to Shrink a 438B Modelhumans& · newshumans&'s Persimmon Fools AI Detectors at Human Rates With 550B ParametersBen Dickson · deep-diveWhat Developers Can Learn From Shopify’s Self-Improving AI Pipeline
