> the only thing you can compete on is how many parameters it takes and how cheaply you can serve that to users.
The problem with this strategy is that it's really tough to compete with open models in this space over the long run.
If you look at OpenAI's homepage right now they're trying to promote "ChatGPT on your desktop", so it's clear even they realize that most people are looking for a local product. But once again this is a problem for them because open models run locally are always going to offer more in terms of privacy and features.
In order for proprietary models served through an API to compete long term they need to offer significant performance improvements over open/local offerings, but that gap has been perpetually shrinking.
On an M3 macbook pro you can run open models easily for free that perform close enough to OpenAI that I can use them as my primary LLM for effectively free with complete privacy and lots of room for improvement if I want to dive into the details. Ollama today is pretty much easier to install than just logging into ChatGPT and the performance feels a bit more responsive for most tasks. If I'm doing a serious LLM project I most certainly won't use proprietary models because the control I have over the model is too limited.
At this point I have completely stopped using proprietary LLMs despite working with LLMs everyday. Honestly can't understand any serious software engineer who wouldn't use open models (again the control and tooling provided is just so much better), and for less technical users it's getting easier and easier to just run open models locally.
In the long run maybe but it's going to take probably 5 years or more before laptops such as Macbook M3 with 64 GB RAM will be mainstream. Also it's going going to take a while before such models with 70B params will be bundled in Windows and Mac with system update. Even more time before you will have such models inside your smartphone.
OpenAI did a good move with making GPTo mini so dirty cheap that it's faster and cheaper to run than LLama 3.1 70B. Most consumers will interact with LLM via some apps using LLM API, Web Panel on desktop or native mobile app for the same reason most people use GMail etc. instead of native email client. Setting up IMAP, POP etc is for most people out of reach the same like installing Ollama + Docker + OpenWebUI
App developers are not gonna bet on local LLM only as long they are not mainstream and preinstalled on 50%+ devices.
The problem with this strategy is that it's really tough to compete with open models in this space over the long run.
If you look at OpenAI's homepage right now they're trying to promote "ChatGPT on your desktop", so it's clear even they realize that most people are looking for a local product. But once again this is a problem for them because open models run locally are always going to offer more in terms of privacy and features.
In order for proprietary models served through an API to compete long term they need to offer significant performance improvements over open/local offerings, but that gap has been perpetually shrinking.
On an M3 macbook pro you can run open models easily for free that perform close enough to OpenAI that I can use them as my primary LLM for effectively free with complete privacy and lots of room for improvement if I want to dive into the details. Ollama today is pretty much easier to install than just logging into ChatGPT and the performance feels a bit more responsive for most tasks. If I'm doing a serious LLM project I most certainly won't use proprietary models because the control I have over the model is too limited.
At this point I have completely stopped using proprietary LLMs despite working with LLMs everyday. Honestly can't understand any serious software engineer who wouldn't use open models (again the control and tooling provided is just so much better), and for less technical users it's getting easier and easier to just run open models locally.