We have sub-agents at home

At work I get unfettered access to gpt 5.4 and sonnet, so I'm quite used to spawning sub-agents to go crazy on a repo and split up tasks. At home I am VRAM poor and like to run the models locally for my own enjoyment. Almost every single sub-agent extension/implementation does not account for any of the restrictions imposed by having 10gb of VRAM and a single slot for a KV cache (thats already quantized). I already work as a developer, so I qwen3.6-35b-a3b tagged teamed a partially vibe-coded fork of an existing sub-agent repository for pi coding agent. This is really only relevant if you: * Use pi coding agent as your harness * Can only run a single LLM at a time with 1 slot via llama.cpp server * Want to use sub-agents without fully reprocessing your prompts after the sub-agent is done Repo is [here](https://github.com/BenjaminBilbro/pi-subagent), feel free to use it or fork it idc. I am also interested in how others around here have dealt with sub-agents on a purely local and VRAM constrained setup. I was also planning to add the ability for sub-agents to be spawned with no previous context, and manage the saving and storing the main context via \`--slot-save-path\` and the \`slots\` endpoint. But the \`.bin\` files produced from that are pretty fat lol Last thing, I've really been enjoying MTP in the main llama.cpp branch and have been getting pretty solid performance from the [Apex Qwen variant](https://huggingface.co/mudler/Qwen3.6-35B-A3B-APEX-MTP-GGUF). Able to run at 175-200k context with q\_8 kv. Getting 200-300 pp and 25-40 tps depending on draft hit rates.