ZooCode is the way
Wish to say to the new ZooCode team that I'm really appreciating this tool. It's been a lot of work to get to a point where it's a serious development tool, but it's starting to all come together now. So much appreciated.
A quick overview for anyone willing to put in a bit of time, for what I think is an affordable, decently fast and accurate coding setup. I'm running Windows 11 with WSL, docker and LM Studio. PC has two RTX 3090's on a Asus ProArt Creator MB, that does 2x PCIe 4.0 x8. Latest release of LM Studio now does MTP, so it can run the Unsloth MTP models that are faster (As of a few days ago). I'm running the biggest model I can fit in 48GB VRAM, Qwen3.6 35B A3B MTP Q8_K_XL with full 261K context. These Qwen models are seriously good. By hooking ZooCode up to a local Docker MCP Tookit, I have the online search tools and some custom docs. This greatly enhances it's capability, pretty close to what Github Copilit is like. Applied the fixed chat template from here: https://huggingface.co/froggeric/Qwen-Fixed-Chat-Templateshttps://huggingface.co/froggeric/Qwen-Fixed-Chat-Templates to the Qwen3.6 models and now they seem more reliable. The MTP models from Unsloth are maybe 40-60% faster than the standard models. I've seen others saying MTP with the MoE models isn't great, but the Unsloth models have the MTP model built in (I believe) and when the same model is select as both main and draft speculative decoding model, it now has been working reliably and faster. I've created a set of local agent instructions which explain the project environment, coding conventions, libraries, etc. In all, this setup is now capable of creating a fairly complex python project with many files, folders, etc. Another thing I've found is to write out the instructions in text, then tell the model to create the model instructions and to ask questions. You then can answer anything that's not clear or specified and the resulting agent instructions for the project seem to work quite well. Also be sure to set the checkpoint feature, it's been quite helpful. A key point for why I use LM Studio is that it has LM Link, so I'm actually coding on my work laptop and LM Studio running locally on my Laptop to connect using LM Link to LM Studio on my home PC. Docker runs locally on the laptop as well as on home PC, two copies each for ZooCode running for home and work setups.
Update: After more testing with bigger workloads I've not been able to fix a 5min timeout from LM Studio that has started occurring with bigger workflows. I've switched back to Unsloth Studio, using OpenAi Compatible connection, same setup for the rest and connect my two machines with WireGuard running on the router and the Windows Laptop. The speed of Unsloth backend seems much faster too. More testing needed, but so far so good.