One issue in picking an AI model is to realize that we’re in a transition period from free and low-cost AI to … something else.
None of the models currently have enough tokens, enough ‘compute’ going forward in the near-to-intermediate future. They’re the victims of their own success. I pay for Gemini ‘pro’, nominally $20 per month, a bit cheaper than that if paid annually, and I got that at half off for the first year. Relative to how much I use it, that’s quite cheap.
My current plan gives me unlimited ‘fast’ and ‘thinking’ mode usage, and while it does restrict my use of ‘pro’, I can count on one hand out many times I’ve hit that limit --- and when I do I shift to ‘thinking’ or just wait to continue the next day with ‘pro’.
I think companies will be forced to change how they charge people for usage, perhaps my current plan will change to one that gives me a fixed amount of tokens per month (a token is a pretty tiny measure of computing power need to run AI). And then charging me extra for tokens used beyond that. Similar to how some phone companies charge for cellular data use.
Think about when Uber and Lyft came on the scene, what maybe 15 years ago? They offered rides at maybe half the cost of the actual ride. Compare your experience (if you did) to using those services then to using them now.
I think that we’re in for the same shift in AI.
I think this makes it more important to pick one LLM and stick with it.
A lot of people are used to ‘model hopping’ --- using only free AI, and if you hit a usage limit with, say, ChatGPT you just shift to Claude.ai or Gemini or what have you.
Going forward this will be less useful. Note that in the past, the difference between ‘free’ and paid was often mostly just speed. Today it’s also about capability. And the limited amount of tokens available for free users will be reduced I think to the point that doing much more than asking a couple (few?) questions might get you to a wall.
Bottom line is that I suspect that people who use AI for much more than the occasional query will find that they need to start paying.
Another alternative will be local LLMs, models that run entirely on your hardware --- more practical for people who have relatively higher end PCs and don’t need the most capable AI models.
If you’ve been on the fence about paying for AI, you might consider picking a model soon and paying annually, in the hope that this will lock in that price for a year.