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I have no idea if costs indeed came down 20x-30x. This claim sounds extremely fancy when AI companies bleed money, and will keep bleeding money in the foreseea

I have no idea if costs indeed came down 20x-30x. This claim sounds extremely fancy when AI companies bleed money, and will keep bleeding money in the foreseeable future. I don't pretend to know the future. Maybe LLMs become economically viable and are the future, maybe not. I don't really care either way, to be frank. And I use LLMs, btw. I pay for a ChatGPT account, but I find it only moderately useful. I always sort of question myself upon renewal date if it is worth the 20 bucks I spend monthly on it. In no small part I keep using it to keep myself up to date on the best practices of using them in case it becomes standard.

simianwords 8mo ago
https://epoch.ai/data-insights/llm-inference-price-trends https://epoch.ai/data-insights/llm-inference-price-trends Do you have any reason to not believe it? It’s expected for costs to come down
- surgical_fire 8mo ago
  The graph you linked seems to compare different OpenAI models in terms of "price per million tokens". I am very skeptical of any financial information that comes from OpenAI. I have no idea how truthful those numbers are, or how creatively they can be collected to paint a rosier future for them. Even if the numbers are truthful, I have no idea how the calculate price there. Is it in terms of cost of compute they rent? Is this cost subsidized or not? Also, I don't know this "epoch.ai" website, I don't know their stance. The website name itself does not inspire my confidence on their reporting of anything related to AI. "Eat meat, says the butcher" vibes and all. You can claim that the AI bleeds money because training is expensive, but inference is cheap. So it will only be financially viable when they stop training models? So they would need to stop improving their capabilities entirely for it to make any sense, is that your claim? Even if I take this claim at face value (and that would take a lot of faith I don't have to give), it doesn't sound as good as you think it does.
  - simianwords 8mo ago
    >To analyze the decline in LLM prices over time, we focused on the most cost-effective LLMs above a certain performance threshold at each point in time. To identify these models, we iterated through models sorted by release date. In each iteration, we added a model to the set of cheapest models if it had a lower price than all previous models that scored at or above the threshold. Can you look at the analysis? It will make it clear. I mean its so obvious because GPT 4 costs way more than GPT 5.2-mini but much worse performance. >Even if the numbers are truthful, I have no idea how the calculate price there. Is it in terms of cost of compute they rent? Is this cost subsidized or not? Do you think they are subsidising 900x or simply that the costs have gone down? Overall you have shown what I feel is extreme skepticism in something that is obvious. You can literally run a model in your laptop that matches an older closed model. Costs are obviously going down, I have shown data. Use your own anecdotes and report. Extreme skepticism in such a way doesn't do any help.
    - surgical_fire 8mo ago
      > Overall you have shown what I feel is extreme skepticism in something that is obvious. I think you show extreme faith in something that is very obscure. For me to believe in the analysis I would need to trust the numbers that the analysis is based upon. I see no reason why I should trust this. What sort of regulatory body or neutral third party inspects those numbers to ensure they are not a fabrication? But you can claim I am a hater if it justifies your worldview. Skepticism is sinful for the believer.
  - Kye 8mo ago
    >> "The dataset for this insight combines data on large language model (LLM) API prices and benchmark scores from Artificial Analysis and Epoch AI." I don't know about Epoch AI, but Artificial Analysis shares its methodology: https://artificialanalysis.ai/methodology https://artificialanalysis.ai/methodology Their chart of inference prices split by benchmark intelligence: https://artificialanalysis.ai/trends#efficiency https://artificialanalysis.ai/trends#efficiency
    - 8mo ago

simianwords 8mo ago

https://epoch.ai/data-insights/llm-inference-price-trends https://epoch.ai/data-insights/llm-inference-price-trends Do you have any reason to not believe it? It’s expected for costs to come down

surgical_fire 8mo ago
The graph you linked seems to compare different OpenAI models in terms of "price per million tokens". I am very skeptical of any financial information that comes from OpenAI. I have no idea how truthful those numbers are, or how creatively they can be collected to paint a rosier future for them. Even if the numbers are truthful, I have no idea how the calculate price there. Is it in terms of cost of compute they rent? Is this cost subsidized or not? Also, I don't know this "epoch.ai" website, I don't know their stance. The website name itself does not inspire my confidence on their reporting of anything related to AI. "Eat meat, says the butcher" vibes and all. You can claim that the AI bleeds money because training is expensive, but inference is cheap. So it will only be financially viable when they stop training models? So they would need to stop improving their capabilities entirely for it to make any sense, is that your claim? Even if I take this claim at face value (and that would take a lot of faith I don't have to give), it doesn't sound as good as you think it does.
- simianwords 8mo ago
  >To analyze the decline in LLM prices over time, we focused on the most cost-effective LLMs above a certain performance threshold at each point in time. To identify these models, we iterated through models sorted by release date. In each iteration, we added a model to the set of cheapest models if it had a lower price than all previous models that scored at or above the threshold. Can you look at the analysis? It will make it clear. I mean its so obvious because GPT 4 costs way more than GPT 5.2-mini but much worse performance. >Even if the numbers are truthful, I have no idea how the calculate price there. Is it in terms of cost of compute they rent? Is this cost subsidized or not? Do you think they are subsidising 900x or simply that the costs have gone down? Overall you have shown what I feel is extreme skepticism in something that is obvious. You can literally run a model in your laptop that matches an older closed model. Costs are obviously going down, I have shown data. Use your own anecdotes and report. Extreme skepticism in such a way doesn't do any help.
  - surgical_fire 8mo ago
    > Overall you have shown what I feel is extreme skepticism in something that is obvious. I think you show extreme faith in something that is very obscure. For me to believe in the analysis I would need to trust the numbers that the analysis is based upon. I see no reason why I should trust this. What sort of regulatory body or neutral third party inspects those numbers to ensure they are not a fabrication? But you can claim I am a hater if it justifies your worldview. Skepticism is sinful for the believer.
- Kye 8mo ago
  >> "The dataset for this insight combines data on large language model (LLM) API prices and benchmark scores from Artificial Analysis and Epoch AI." I don't know about Epoch AI, but Artificial Analysis shares its methodology: https://artificialanalysis.ai/methodology https://artificialanalysis.ai/methodology Their chart of inference prices split by benchmark intelligence: https://artificialanalysis.ai/trends#efficiency https://artificialanalysis.ai/trends#efficiency
  - 8mo ago