Coding on an 8GB 5060, where tuning the GPU/CPU split matters more than tok/s

This person uses local models almost daily for coding and working with local files, on an RTX 5060 8GB with 32GB of RAM, running Windows, Ollama and mostly Qwen models, sometimes with Pi and Aider. The recurring problem is not whether a model can run but getting good performance once the model, the context and other processes compete for limited VRAM.

They have spent a lot of time manually tuning GPU-layer offload and CPU offloading to make larger models usable, finding that a different GPU/CPU split sometimes makes a surprising difference while other times the bottleneck is context processing or waiting on tools and web requests. Their measure of a good coding experience is the model staying responsive, not posting a good tok/s number. It does not replace Claude for everything, but it is genuinely useful for local files, coding experiments and anything they would rather not send to the cloud.

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