Compact, mixed-precision GGUF quantizations of Swift 1.5 Qwen3.8-27B, with Swift-specific refinement using the per-tensor allocations from ISTA-DASLab's GSQ-RCO release. Swift 1.5 builds on Swift 1.0 through post-training focused on long-horizon, agentic and coding tasks, improving overall performance while using fewer thinking tokens. See the original model card for the model's training approach and benchmark results. Those model-level benchmarks are separate from the quantization measurements below. Swift 1.5 uses 58.5% fewer thinking tokens while scoring 0.35% higher than the base, for a 9.18× speed-up on several tasks. Each tier is a single GGUF file. Sizes are decimal GB; runtime…