Qwen3.8 27B Swift

User reports post-training Qwen3.8 27B into Swift-Qwen3.8-27B, achieving 58% fewer thinking tokens and 1.95x speedup while maintaining accuracy. Training used an 8xH100 box with LoRA SFT, On-Policy Distillation, and a token penalizer targeting overthinking patterns. Benchmarks ran at xhigh thinking effort in BF16. GPQA-Diamond: 88.3% vs 88.4% base with 58% fewer tokens; LiveCodeBench v6: 81.6% vs 76.8%; Terminal-Bench 2.1: 65.8% vs 66.7%; MMLU-Pro: 85.0% vs 85.5%; C-Eval: 90.6% vs 90.0%; IFBench: 71.8% vs 73.5%; AIME 2026: 94.0% vs 98.7%; HMMT: 96.0% vs 99.3%; ERQA: 66.3% vs 67.5%. Token savings hold across efforts: xhigh 41%, medium 23%, low 26%.