KVARK Sparkle 1.0 is an Apache-2.0 Qwen3.8-27B tune that thinks up to 67% less for about the same accuracy

Egzakta AI Lab's first open-weight model, posted Nov 2 in BF16, FP8 and GGUF with an MTP head for speculative decoding, cuts median reasoning tokens 34–67% across five benchmarks and answers in 13.7s versus 28.1s for Qwen3.8-27B on one H200, with accuracy within a point except a +5.3 on a 50-problem LiveCodeBench subset. All numbers are the lab's own, and the GGUF runs locally via llama-server -hf Egzakta/Kvark-Sparkle-1.0-27B-GGUF:Q4_K_M.