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Proton's very biased article on Deepseek
(lemmy.ml)
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this post was submitted on 31 Jan 2025
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It might be trivial to a tech-savvy audience, but considering how popular ChatGPT itself is and considering DeepSeek's ranking on the Play and iOS App Stores, I'd honestly guess most people are using DeepSeek's servers. Plus, you'd be surprised how many people naturally trust the service more after hearing that the company open sourced the models. Accordingly I don't think it's unreasonable for Proton to focus on the service rather than the local models here.
I'd also note that people who want the highest quality responses aren't using a local model, as anything you can run locally is a distilled version that is significantly smaller (at a small, but non-trivial overalll performance cost).
You should try the comparison between the larger models and the distilled models yourself before you make judgment. I suspect you're going to be surprised by the output.
All of the models are basically generating possible outcomes based on noise. So if you ask it the same model the same question five different times and five different sessions you're going to get five different variations on an answer.
You will find that an x out of five score between models is not that significantly different.
For certain cases larger models are advantageous. If you need a model to return a substantial amount of content to you. If you're asking it to write you a chapter story. Larger models will definitely give you better output and better variation.
But if you're asking you to help you with a piece of code or explain some historical event to you, The average 14B model that will fit on any computer with a video card will give you a perfectly serviceable answer.