I have Qwen 3.6 27B bf16 llly hosted and am consuming it with VSCode Insiders using Github CoPilot and it's honestly great, but i notice it doesnt actualy make plan.md files and can sometimes not use the tools as well as the hosted models.
Has anyone figured out a killer prompt to use for this coding harness that really makes it shine?
I finally got around to installing Unsloth Studio and am giving it a whirl on my Windows machine. I have an RTX6k and am trying to load the latest QWEN MTP model you guys created. However no matter what I do, all models are loading in RAM instead of the GPU.
From what i see online it means there's a cuda driver mismatch most likely. But i installed 12.9 and updated all my environment variables. So I'm not sure why this is still happening.
Any thoughts or help?
I recently did my analysis for Github Copilot and was shocked that my "average usage" on the $40 dollar plan was going to amount to about $500 dollars a month. Whats crazy about that is if you purchase an RTX6000 with credit, the payment is only about $420 dollars a month.
With Qwen 3.6 27B, I am able to build out a feature in Plan mode with VSCode Insiders Edition and then run through the implementations with no issues. Running this model at bf16 gives amazing results because of the quality of the harness and it's cheaper and I can abuse my token use without any worries.
Other than the most difficult of planning sessions, I think that we've hit the point where local models are more than good enough and they price point is cheaper than hosted models. You can get cheaper hosting if you're only using qwen but with the perks of privacy and owning hardware, it just makes sense to purchase the card if you're going to be stuck with a 500 dollar bill regardless.
So in response to the Great Token Reconning of 2026, I decided to try out Qwen 3.6 as a daily driver, and although it's only been about a day, I have to say I'm thoroughly impressed.
I had to download the VSCode insiders edition and set up the local models to support - super easy. Then I messed around with Gemma 4 and Qwen 3.6 (served with LM Studio) while performing typical tasks as I build out an app that does a lot of data mining and web scraping.
After trying out all the versions of the two models with the different quants, there is a clear winner: Qwen-3.6-27B-q8_k_xl by Unsloth.
I AM SO IMPRESSED! The token generation can be a tad bit slow, but the truth is, I was seeing long delays even when I was using Github Copilot hosted models. It felt about the same speed wise overall, maybe a touch slower than hosted. But whats impressive is with appropriate tool calling this little dense model can handle its own just fine.
To be clear, I dont think this it can work at the feature level like Opus 4.6 could. You cant just say "Hey implement this feature" - vibe coders and non-coders wont survive with this most likely. There were a few times where I had to steer it to improve it's code quality and approach, but functionally it was nailing it.
If you always do a Plan round first and really work out all the details, then it will get there, and then implement it without issue. If you have a decent grasp of systems architecture this is perfectly hitting that "good enough" status for a local model. I have been plugging away all day and havent used a single API token.
Now I need another RTX6000 so I'm not fighting with my agents for compute 😝
I have been creating a system that generates Inheritance Leads the day a death becomes public. This is pre-probate and done by scanning all obituaries across the country. However I am a computer/data guy, not a realtor - and it would seem this is a difficult or specialized slice of the market.
My question is does anyone out there have experience with working these leads? Would love to get insight into how this is best approached and what things, tools or info would make the process easier.
If anyone out there has experience I will trade high quality leads for consultation. Thanks for reading!