Swift is a family of efficient reasoning models from UkisAI built on Qwen, which cuts thinking tokens by penalizing pathological overthinking and restores accuracy via reinforcement learning. Recent coverage includes Swift Flash Next reducing thinking tokens by 63.4% with a 1.8x speedup, Swift1.5 27B cutting 58.5%, and a third-party Aider evaluation showing ThinkingCap and Swift fine-tunes cut Qwen3.8-27B's median reasoning tokens from 12,547 to about 7,400. A community user also released Swift 1.5 27b, claiming Swift Qwen is faster.
Swift 1.5 27b released: Swift Qwen gets fasterA community user released Swift 1.5 27b, claiming Swift Qwen is faster. The post offers no specific benchmarks or technical details, only enthusiasm for the update.
UkisAI Releases Swift Family of Efficient Reasoning ModelsUkisAI launched the Swift family of reasoning LLMs built on Qwen, cutting thinking tokens by penalizing pathological overthinking and restoring accuracy via RL. Swift Flash Next reduces thinking tokens 63.4% with 1.8x speedup; Swift1.5 27B cuts 58.5% with slightly higher scores; Swift Bonsai 2 cuts 39.8%. API, demos, and quants are provided.
Benchmark: ThinkingCap vs Swift vs Qwen 3.8-27BA third-party Aider evaluation found that ThinkingCap and Swift fine-tunes cut Qwen3.8-27B's median reasoning tokens from 12,547 to about 7,400, a roughly 40% reduction matching their model cards, with first-try pass rates of 27.1%-30.8% and retry pass rates of 75.7%-77.6%, showing no meaningful performance loss.
The A.I. Daily