Qwen3.6 27B
on Unknown GPU · llama-cpp-python · 32,768 ctx
Use cases
codingtool-use
Summary
User benchmarks Qwen 3.6 27B across BF16, Q4_K_M, and Q8_0 GGUF quant variants with llama-cpp-python using Neo AI Engineer, on HumanEval, HellaSwag, and BFCL.
Q4_K_M is the best practical variant: 1.45x faster than BF16, 48% less peak RAM, and a 68.8% smaller model file.
Function calling scores are nearly identical to BF16.