Kapitsa 0.2 brings KFlash speculative decoding to Apple Silicon, tops self-run benchmark
Kapitsa, an open-source inference engine for Apple Silicon aimed at Qwen and Nemotron models, released version 0.2 with a new speculative decoding method its developer calls KFlash, announced in a r/LocalLLaMA post. KFlash checks a best-first tree of the draft model's candidate tokens in one pass, whereas the comparison DFlash2 method checks a single chain and stops at the first wrong guess. In the developer's own benchmarks on a MacBook Pro M4 Pro with 48GB, Kapitsa reported 63 tokens/s on Qwen3.8 27B versus 53 tokens/s for Splash 1.4.0 with DFlash2, and 95 versus 62 tokens/s on Qwen3.5 4B on an M1 Pro 16GB machine; the author cautioned readers not to trust benchmarks and to run their own.
The post offers a side-by-side comparison of speculative decoding approaches across several local inference engines on consumer Macs, while its author explicitly warns that the numbers are self-reported and should be reproduced independently.