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Comment by digdugdirk

3 hours ago

Not really - fine tuning can be done on much lower tier hardware, with much smaller datasets. With a model like Qwen 3.8 27B as the core, a small fleet of LoRA adapters for whatever specific use cases you need would be incredibly competitive with the current frontier. Sure, future frontier models will likely continue to improve, but will people need them for everyday usage? I'd wager not. Unfortunately, my wager is dwarfed by OpenAI's and Anthropic's.

I’d love to see examples of this. Learning how to enhance local models to stay competitive would be a great skillset to develop.

Can you just keep fine-tuning indefinitely? I don't really know but it feels like eventually that might start impinging on the model's abilities?