every weight matrix, including the 250,624-token embedding table and output head, is Q40 (llama-quantize --pure), made from IFM's BF16 GGUF. The official GGUF repo has no Q40 file. On ARM CPUs with the i8mm or dotprod instructions llama.cpp runs Q40 faster than the K-quants: on a Snapdragon phone this file reads prompts 1.4-1.7x as fast as IFM's Q4KM, but generates only 1.04-1.11x as fast, and it is 9 % smaller. I tested it as an on-device chat model for an Android voice assistant (llama.cpp, CPU only). The file name follows the naming of IFM's GGUF repo (K2-Horizon-4B-.gguf). K2-Horizon family (3.7B core parameters plus a large vocabulary; 5.06B parameters in the file). All credit for the…
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Bpmatt
bpmatt
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