Qwen 3.5 9B (Q4_K_M)

Qwen 3.5 9B in its Q4_K_M quantization is distributed as a GGUF-format model designed for local inference via llama.cpp. The Q4_K_M tier balances model size against computational efficiency, making it well suited for running on consumer hardware such as laptops with unified memory. A third-party benchmark using llama.cpp build b4500 on a macOS Apple Silicon machine with 16GB of unified memory demonstrated approximately 4.6 tokens per second when invoked directly through the llama.cpp command-line interface, indicating that this quantization can sustain responsive interactive generation on modest hardware.

Because Qwen 3.5 9B (Q4_K_M) ships as an open GGUF artifact, it can be loaded directly into llama.cpp with minimal wrapper overhead, allowing users to control inference parameters explicitly. In contrast, the same model run through LMStudio 0.3.x on identical hardware produced roughly 2.4 tokens per second, a gap attributed to default configuration choices in higher-level wrappers rather than differences in the underlying engine. This makes the raw llama.cpp path attractive for developers who want to maximize throughput on local hardware, while still leaving the option to use friendlier interfaces when convenience outweighs raw speed.