Qwen 3.5 35b on 8GB Vram for local agentic workflow

Recently I had been using Antigravity for mostly vibe coding stuff that i needed. But the limits have hit hard. (have google ai pro yearly plan)

So I pivoted to local LLMs to augment it. After extensive testing of different models I have settled on Qwen 3.5 35B A3B Heretic Opus (Q4_K_M GGUF).

My specs are: (Lenovo Legion)

• CPU: i9-14900HX (8 P-Cores, E-cores disabled in BIOS, 32GB DDR5 RAM)
• GPU: RTX 4060m (8GB VRAM)

Currently I am getting about 700t/s for prompt processing and 42t/s for token generation which is respectable for my 8gb vram gpu. Here are the settings i settled upon after some testing:

Using llama cpp:

-ngl 99 ^

--n-cpu-moe 40 ^

-c 192000 ^

-t 12 ^

-tb 16 ^

-b 4096 ^

--ubatch-size 2048 ^

--flash-attn on ^

--cache-type-k q8_0 ^

--cache-type-v q8_0 ^

--mlock

After some research the closest thing to Antigravity I could find is Cline in VSCode. I use kat-coder-pro for Plan and qwen3.5 for Act mode. Is this setup better or should i stick to google gemini 3 flash in antigravity which has plenty of limits and is pretty fast? I dont care much about privacy, only about getting work done smoothly. Any suggestions for potential improvement?

Thanks.