GPT4All user seeks multi-agent setup

Hot take: this is more an orchestration problem than a model problem. GPT4All already exposes a local API server, so the fastest path is a small agent runner that calls localhost, saves outputs, and feeds them back into a judge model. GPT4All's OpenAI-compatible localhost endpoint makes it easy to plug into agent frameworks or a lightweight Python script. With 40GB of system RAM but only 6GB of VRAM, the likely sweet spot is a quantized 7B/8B-class model on the GPU and larger models mostly offloaded to CPU; that's an inference from the hardware, not a product claim. Multi-agent experiments usually work best when one model generates, another critiques, and a simple log file or SQLite table captures the handoff. If the goal is productivity rather than tinkering, a local host plus workflow tool will beat juggling multiple chat windows by hand.