I’ve been using Claude for coding for quite a while, but it eventually became a bit too expensive for the amount I was using it. I recently got myself a 5090 and thought I’d give local models a serious try. I already have VS Code set up, but I’m still trying to figure out what the “right” workflow is. One of the first things I wanted to do was convert a small application I have written in PowerShell over to Python, while keeping the existing GUI and functionality as close to the original as possible. I tried Cline first, but it didn’t really manage to get there. Then I used the Copilot chat inside VS Code with the model left on Auto, and surprisingly it handled the conversion pretty easily. That made me curious, so I tried switching Copilot from Auto to Qwen3-Coder. Interestingly, Qwen struggled with the exact same task where Auto had done a pretty good job. Now I’m wondering how much of this comes down to the actual model and how much comes down to the agent/environment around it. For those of you using a 5090 or similar hardware for local coding, what has actually worked well for you? I’m particularly interested in setups where you can throw an existing project at the AI and let it understand the codebase, make changes across multiple files, run things, debug, etc., rather than just asking it to generate individual pieces of code. I’m not really interested in benchmark results — I’m more interested in what you’ve found reliable in actual day-to-day development. Would love to hear what you’re using and how your setup/workflow looks. submitted by /u/Efficient_Raisin7645
Originally posted by u/Efficient_Raisin7645 on r/ArtificialInteligence