Local LLM Executor + cloud Planner

In my experience, local 35 a3b models are very fast and capable of handling clearly defined tasks: making code changes, collecting and analyzing logs, interacting with complex systems like Unity via the cli pipeline, and even viewing images and screenshots to identify visual issues. They can handle a huge amount of menial work.

However, they are noticeably less effective at handling logic, architectural decisions, and bug hunting. I recently tried GLM 5.3 and was impressed by its amazing ability to handle complex code, logical thinking and ability to implement algorithms from scientific publications. Debugging elusive bugs were also impressive but tedious. Even with its low cost, log analysis and iterations in tooling easily burn through $5 per hour.

So I thought it would be great to organize a workflow with sub-agents, using a cloud model for thinking and writing code snippets, and a local model for implementing the plan and, most importantly, collecting testing and debugging reports. Has anyone tried this hybrid agent mode? I'm going to try kilocode, cline, or writing an extension for pi agent (maybe one already exists?). What do you think?