Assuming you’re willing to drop a fat stack of cash on the upcoming Mac m5 ultra with 512 gb unified memory, you can even run it locally, quantized to 4 bit. Whether it’s even slightly reasonable, well, my wife would probably skin me alive but maybe yours is more understanding.
* LLM usage is new for the world
* Models are evolving quickly with high worldwide competition
* Hardware is evolving despite RAM shortages
Is investing a huge sum of money in equipment for local inference a wise use of money? Or are M5 Ultra and equivalently priced local inference hardware future-proof enough to be worth it relative to how the market is evolving? Maybe it’s all a question of what you’d spend otherwise on serverless or dedicated GPU spend…
That said, when I bought my pair of Sparks, the best model I could run on it was GPT OSS 120B. That has an AA score of 24.
Today, the best model I can run on them is GLM 5.3 Flash at Q4, AA score 57. Just still out on GLM 5.3 mixed quant.
So from that perspective, they are many times better value than when I bought them, and will likely continue to increase in value.
I'm happy with all of the competition in the APIs on openrouter... I watch that like I used to watch the stock markets, lol. It's great fun.
Though I appreciate how good it is at "solid" grunt work and at that price (in fact I am paying the grandfathered subscription price; mostly).
I am planning to let go for my Claude AI subscription which I now use only for "planning" and maybe use that via Open Router as PAYG (at to try how it ends up). But god glm is bad at "talking" and "responding" anything prose. Not only quality but it's almost impossible to tune it and make it let go of its habits and biases and enthusiasms which often result in too many too and fro.
So I sometimes wonder at what point that starts becoming the cost and mental hassle. Maybe it's not there for me yet.