Qwen3.8-27B with 24GB VRAM (RTX 5080 + 3070) - which quant & settings?

I’m a beginner with local LLMs and I’m wondering how best to approach running Qwen3.8-27B (medium reasoning) with 24GB of total VRAM.

My PC has an RTX 5080 16GB + RTX 3070 8GB, 32GB DDR5-6000 CL30, Ryzen 9800X3D 8x core, and a 2TB NVMe SSD.

I want to run Qwen3.8-27B purely for simple coding work: changing text, style tweaks, component edits, that sort of thing. I don't need to use it for problem solving, planning, reviewing, etc - I will continue using Claude/Codex for those tasks.

If simple prompts take longer than ~30 seconds to complete, I'm likely going to find myself going back to Codex - so I'm hoping this speed is achievable without noticeably lobotomising the model? Also, I would like to avoid offloading to CPU/RAM.

I've done some research and I believe Unsloth UD-Q4_K_M using llama.cpp is my best bet? Any suggestions for what kind of configuration I should be using?