A personal review of using the Qwen 3.8 model for agentic coding, praising its ability to handle complex tasks like integrating llama.cpp with Godot while noting issues with looping.
So, im 50 and autistic. I learned C++ in college when I was young and didnt really ever use it that much. I also learned a bit of assembly from using cheat engine for game hacking (dont worry! single player or private servers!) which meant I got a little LUA experience. I've always disliked coding. Its such a "bang head against wall" type activity but I got into it because its pretty cool being able to make a computer do what you want. This entire attitude died a LONG time ago because coding wasnt my thing. Could be my autism or whatever, could be I suck at it, could be I just plain dont like it. In the early days of AI I used to ask models to make simple stuff I could copy and paste, eventually it got to the point I could use a local model to clone a repo and build it. This shit is SO much fun. Ok so to the point. My game has 3d, path finding, routines and a whole bunch of other stuff. one of the more tricky parts is the game uses an LLM. I've been banging my head against a wall trying to get all of this working and today I decided to pull in an LLM which happened to be qwen 3.8. I explained the issues I was having and within 10 minutes it had fixed everything. It wasnt perfect but it involved llama.cpp and a custom addon on godot. So my thoughts in order of impact of using the model. 1.When it works it REALLY god damn works. This thing codes so hard, one shots even complex shit that can involve llama.cpp. I've never seen a model code so well. something on my body went really small the first time I saw it code. 2.Right now its VERY prone to loops. I've had sessions which have just gone south after 2-3 prompts and it just repeats itself violently. (watch those eyes). hoping this will clear up. 3.The previous models over thinking is gone. 4.Im using the official token plan from alibaba and the speed of this thing is nuts. 5.I never planned for a fifth point. Not sure why this is here. So, just some casual observations from me. Overall? im chuckling while writing this but honestly, the model needs a bunch of tuning but right now its stupidly powerful when it works. I've never seen a model work with such complex code and still just walk through it like its nothing. Wish I could run this on my crappy 3060 ti though. Maybe in a few years ;)
User reports positive experience with Qwen 35b a3b for agentic coding tasks, noting it outperforms Gemma4 26b in their use case and works well for demo/data analytics, especially in agentic mode versus chat.
Qwen releases the open-weight Qwen3.6-27B model on Hugging Face, featuring improved stability, agentic coding capabilities, and thinking preservation for better developer productivity.
A user reports that Qwen3.6 35B A3B outperforms other local models like Gemma4 and GLM 4.7 Flash REAP for agentic tasks, though occasional loops still occur.
Qwen 3.6 27B is praised as a powerful local AI model that outperforms expectations for general intelligence, suitable for practical tasks like code generation, and runs easily with llama.cpp.
A user asks for community input on the practical usefulness of qwopus compared to qwen3.6 27b, particularly for agentic coding tasks, reporting mixed opinions and minimal personal differences in testing.