Qwen2.5 1.5B (0.9B active) MoE

User reports Qwen2.5-1.5B-MoE-A0.9B at 253 t/s text generation on an RTX 4060 8 GB, up 32% over the dense Qwen2.5-1.5B at 191 t/s. Setup is llama.cpp with Q4_K_M GGUF on both models; CPU generation was 77.5 t/s for the MoE versus 54.9 t/s for the dense model, a 41% gain. Perplexity is about 40% higher for the MoE (WikiText-2 14.63 vs 10.41, C4 22.88 vs 15.76) and zero-shot mean acc_norm drops from 0.565 to 0.462, with the largest losses on ARC. The user calls this a proof of concept, noting quality is roughly in Qwen2.5-0.5B range and that the GGUF is larger (1.1 GB vs 0.9 GB) because llama.cpp's MoE architecture needs an untied output head.