Qwen 3.6 27B on 24GB VRAM: backend comparisons, quant choice, and settings

Qwen 3.6 27B on 24GB VRAM setup: backend comparisons, quant choice and settings (llama.cpp, ik_llama.cpp, BeeLlama, vllm)

The author tested Qwen 3.6 27B on an RTX 3090 24GB and kept ik_llama.cpp with Qwen3.6-27B-MTP-IQ4_KS.gguf; at 156k context with q8_0 KV and MTP, a ~5.9k-token prompt plus 1024-token output reached about 1261 tok/s prefill and 72.9 tok/s decode, while vLLM lacked a clean single-card long-context run.

Why it matters: HKR-H/K/R all pass: this is a first-person local inference benchmark with concrete VRAM, quant, context, and speed numbers. Its reach is narrower than a model release, so it sits at the featured threshold.