Beginner gets stuck on Ollama agent setup

This is the classic local-LLM beginner trap: three layers, one goal, and no clear line between model host, model choice, and agent UI.

• –Ollama is the local inference/runtime layer, while Roo Code is the coding-agent frontend; mixing those roles up makes the setup feel broken even when it is not.
• –The hardware is workable for local experimentation, but model size and quantization matter more than raw VRAM bragging rights.
• –Qwen3.5 MoE may be overkill or awkward depending on the exact quantized variant, so a smaller model is often the better first sanity check.
• –The right progression is usually: confirm Ollama runs one model cleanly, then connect Roo Code, then tune prompts, tools, and context limits.
• –This is useful community signal, but it is troubleshooting content, not a launch or announcement.