SemiAnalysis has calculated how big that gap really is. After testing subscription tiers from both OpenAI and Anthropic – running long-horizon coding and agentic tasks until weekly...
The actual cost to OpenAI is likely much less. The number in the article is calculating the API cost that a fully maxed out subscription would incur theoretically.
The API token cost, however, is far above the actual computational cost.
The actual price is hard to really know, but I think training should also factor in. The hype of LLMs is based on the fantastical idea of continunous improvement forever, so you need to keep training. Even ignoring the hype part, you still need to retrain simply to update the data inside the LLM.
I guess we’ll only know for sure after the crash/readjustment.
I disagree - the analysis takes as a basis a very, very generous margin of 75% on API prices. There is no way they have that much of a margin, this is wishful thinking.
And every single user who maxes out their 200$-subscription burns more cash than they take in from 70 subscriptions that lie dormant.
I was talking to one of our cloud architects at work yesterday. They did a test and just ran in “asdf” to a chat prompt, and were able to trace the costs. It was 12 cents.
I could totally see AI costs getting out of control very quickly. Doing something like a Copilot formula in an Excel spreadsheet is easily going to run up hundreds of dollars of costs eventually.
It’s a 200 dollar subscribtion. Are any actual users around that can provide info on how actively they are using it? I would feel that at 200 dollars they give you loads of headroom.
The actual cost to OpenAI is likely much less. The number in the article is calculating the API cost that a fully maxed out subscription would incur theoretically. The API token cost, however, is far above the actual computational cost.
The actual price is hard to really know, but I think training should also factor in. The hype of LLMs is based on the fantastical idea of continunous improvement forever, so you need to keep training. Even ignoring the hype part, you still need to retrain simply to update the data inside the LLM.
I guess we’ll only know for sure after the crash/readjustment.
I disagree - the analysis takes as a basis a very, very generous margin of 75% on API prices. There is no way they have that much of a margin, this is wishful thinking.
And every single user who maxes out their 200$-subscription burns more cash than they take in from 70 subscriptions that lie dormant.
I was talking to one of our cloud architects at work yesterday. They did a test and just ran in “asdf” to a chat prompt, and were able to trace the costs. It was 12 cents.
I could totally see AI costs getting out of control very quickly. Doing something like a Copilot formula in an Excel spreadsheet is easily going to run up hundreds of dollars of costs eventually.
It’s a 200 dollar subscribtion. Are any actual users around that can provide info on how actively they are using it? I would feel that at 200 dollars they give you loads of headroom.