Dansday
I’ve been experimenting more with running local language models lately. The whole idea of having a capable AI that runs entirely on my own machine, without sending data to the cloud, has always appealed to me. It’s about privacy, control, and frankly, the satisfaction of seeing it work. My main workhorse for this has been my NVIDIA RTX 3070, which, while not the latest and greatest, still packs a decent punch.
Recently, I decided to test out Qwen's 2.5 Coder model. I was curious to see how a modern, code-focused model would perform on hardware that isn't exactly top-tier for AI in 2026. The RTX 3070 has 8GB of VRAM, which is a significant constraint for many of the larger models out there, so I was managing my expectations.
The setup was straightforward. After getting the model running, I started throwing some medium-complexity coding tasks at it. I'm not talking about building an entire application from a single prompt, but more practical, day-to-day developer work. Things like refactoring a complex function, generating boilerplate for a new component, or writing a suite of unit tests for an existing class.
I have to say, I was genuinely impressed with the results. The model did a great job. The code it generated was not only functional but also surprisingly clean and idiomatic. It handled context well within the scope of the task and saved me a considerable amount of time. The speed was perfectly usable; there was a slight delay for generation, but it wasn't disruptive to my workflow. For these kinds of medium-sized, self-contained tasks, it felt like a real productivity booster.
This experiment has me convinced that local AI for development is becoming incredibly viable, even without the absolute latest hardware. While cloud-based models still have their place, especially for massive-scale tasks, the ability to run a competent coder model locally on a card like the RTX 3070 changes the game for everyday coding assistance. It's a powerful and private way to augment your workflow, and I'm excited to see how much further this can go. I don't have any specific performance metrics or projects to share on this yet, as this was more of a personal exploration, but it's definitely an area I'll be investing more time in.