Have you tried other local models?

The 14B Q4_K_M needs 9GB, but Q3_K_M is 7.3GB. But you also need some room for context. Still, maybe using `--override-tensor` in llama.cpp would get you a 50% improvement over "naively" offloading layers to the GPU. Or possibly GPT-OSS-20B. It's 12.1GB in MXFP4, but it’s a MOE model so only a part of it would need to be on the GPU. On my dedicated 12GB 3060 it runs at 85 t/s, with a smallish context. I've also read on Reddit some claims that Qwen3 4B 2507 might be better than 8B, because Qwen never released a "2507" update for 8B.