| ▲ | TrackerFF 3 days ago |
| But the question is how much are people willing to pay for AI. I use AI every day at work, but I only pay $20. That's the most I will ever want to pay. And, so far, it gives me everything I need. If OpenAI or Anthropic suddenly said "Sorry, the game is up. You'll have to pay $100/month now", I would 100% look into cheaper Chinese solutions. I suspect the AI subscription (or API) economy is whale economy. You have a small, small percentage of users that are happy to pay whatever it takes - while the vast majority will either use the free tier, and then the next group will pay for the cheapest or next cheapest subscription. EDIT: And I'll echo what another user wrote here. The VAST majority of office users around the world don't work for tech companies flush in cash. Even adding something like $20 - $100 subscriptions to every user is a serious enough financial obligation that it needs to go through budget planning / boards. Even more so for all the government workers around the world. |
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| ▲ | cm2187 3 days ago | parent | next [-] |
| The video quotes sales of $2.5 trillion a year to payoff those investments. What workforce you divide it by is a bit up in the air, but let's use 500 millions, which is basically 100% of the workforce of US + Europe + some change. That gives you around $500 a month per employee (from hedge fund manager to flipping burgers at McDonald's). And there will be competition. I see zero moat right now. The user specific part of the state of the model sits outside of the control of the model (it is basically my code base, or my prompts, all of which I can transfer to any competitor). |
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| ▲ | amluto 3 days ago | parent [-] | | Speaking of user experience: OpenAI has some pretty cool tools, some of which even have decent UX. But I’m amazed that anyone can get real work done with the first party web UI. It is UNBELIEVABLY LAGGY. It makes GitHub seem snappy. It scrolls to a black screen and slowly populates later. It takes tens of seconds to load conversations. On the rare occasions that I’ve tried the fun “ask Pro mode a math question” I think I’ve spent 15 minutes waiting for content to populate in the UI. Oh, and all the obvious features like forking a chat either don’t exist or are somehow hidden. This is on a top-of-the-line client machine. Maybe other users are doing something differently or are being served a different front end JavaScript blob? | | |
| ▲ | jurgenburgen 2 days ago | parent [-] | | The iOS app is hot garbage as well. The list of old chats will have topics randomly jumping around which makes it really annoying to try to choose the scheduled task that notified you. |
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| ▲ | jrflo 3 days ago | parent | prev | next [-] |
| But AI use translates directly to time savings (if it works). You only need 1-2 hours of time savings per employee per week to break even on a $100/seat/month subscription. |
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| ▲ | oblio 3 days ago | parent | next [-] | | In the US. With how much they've invested in AI they need the entire planet to pay, and pay lots. What's the capex expenditure of Magnificent 7 just this year? Close to $1tn? | | |
| ▲ | WarmWash 3 days ago | parent | next [-] | | They need it to be roughly as popular as first world cell phone usage for a 5-7yr ROI. | | |
| ▲ | oblio 3 days ago | parent | next [-] | | 1. Cell phone usage was never free. 2. Cell phone usage was always localized. You had local telcoms and that was about it. Deutsche Telekom Germany didn't have to compete all the time with NTT Docomo Japan. And there are probably 20 other economic differences I'm missing. | |
| ▲ | saghm 2 days ago | parent | prev [-] | | Everyone uses cell phones. Not everyone has a job where paying this much for these tools would be worthwhile for their employer. |
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| ▲ | jrflo 3 days ago | parent | prev [-] | | Yeah, they may be over built for sure, I'm just saying the demand is there. | | |
| ▲ | oblio 3 days ago | parent [-] | | Demand for the internet was there but it still took 10+ years and a big economic crash to get there. |
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| ▲ | gedy 3 days ago | parent | prev [-] | | That's not how people mentally price things though, i.e. "streaming is so much cheaper than the movie theaters!", etc | | |
| ▲ | memonkey 2 days ago | parent [-] | | How do people mentally price things. I'm on the fringe but I'm willing to pay $60 for a AAA 60 hour game that I'm positive I won't finish but am find if I get 6-10 hours out of it. |
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| ▲ | stackbutterflow 3 days ago | parent | prev | next [-] |
| To put it into perspective if we consider that US salaries are 3 to 5 times those of other "rich" countries then it's already a 60 to 100 dollar subscription for the next richest part of the world. |
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| ▲ | fallingbananna 2 days ago | parent [-] | | I have a devils advocate argument: AI spend doesn't need to scale with salary. If a company was OK with paying 10k a month for an employee in the US because they considered their work more valuable. And the same company is only willing to spend 300 per month on someone in a 3rd world country, because they consider the work to be lower quality. Wouldn't it be reasonable to consider a situation where the same company would be willing to only spend 100 per month more on the 10k employee to make them a bit faster. At the same time be willing to spend 700 per month on the 300 employee, if it levels out their capabilities and makes them nearly as valuable as the 10k employee? --
This argument is riddled with assumptions, but I do feel like it's one possible direction that some companies might try to take. |
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| ▲ | porridgeraisin 3 days ago | parent | prev | next [-] |
| > Even adding something like $20 - $100 subscriptions to every user is a serious enough financial obligation that it needs to go through budget planning / boards I doubt that. In my tiny town in India, office workers use the 1800 INR (20$) plans. 1800 INR/month is like... 4% of the salary these guys get. And since this is mostly MS-office and windows explorer and chrome based stuff in very small, non-tech companies, it pays for itself in literally a day. If they _could_ pay less they would. After all they pirate MS office. But the cheap chinese plans dont have any distribution, whereas OpenAI seems to have effectively marketed to them via IPL ads and such. No one there even knows about deepseek. It also doesn't help deepseek and such are focused on the coding market. No multimodal, office plugins, etc. For personal stuff, people there use Meta AI - mostly because it is directly available in whatsapp and these days they are pushing it by adding a dedicated button for it right on the home page. Regardless, they still call it "chatgpt". OpenAI brand is unmatched. |
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| ▲ | rdedev 3 days ago | parent | next [-] | | Remember that 20$ is a subsidized rate openai is currently willing to provide. Once that goes down you think these guys would be willing to pay token based billing charges ? | | |
| ▲ | porridgeraisin 3 days ago | parent | next [-] | | It is not going to go away. Rather they have doubled down and opened 399 INR/mo (4$/mo) plans that as of late have GPT 5.6 Luna. The reason this works is that you get lesser inference time compute used for queries on these cheaper plans which makes it sustainable and this is enough for the tasks these guys do. And some local telcos are bundling this subscription as well, so most people just get it for "free". For example, I get Google AI Pro for free with my 350 INR/mo telco plan. | | |
| ▲ | rdedev 3 days ago | parent [-] | | These companies have spent billions of investor dollars and they will need to recoup that cost soon. And then show year over year growth on top of that. Unless they can massively scale down training and inference cost or implement AGI I don't know what their plan is. Just provide a subsidized plan for the next 10 or 20 years? Their costs are directly proportional to the amount of tokens the LLM produces. How is a monthly subscription plan supposed to account for such costs? | | |
| ▲ | carlosjobim 3 days ago | parent | next [-] | | > These companies have spent billions of investor dollars and they will need to recoup that cost soon. And then show year over year growth on top of that. Or else? | | |
| ▲ | jurgenburgen 2 days ago | parent [-] | | > Or else? Their investors will throw the CEO under the bus and hire a new one that will enshittify it enough to make them money. | | |
| ▲ | carlosjobim 2 days ago | parent [-] | | Oh, I didn't know it was that easy to make trillions of dollars in profit. You say there fella that they just need to shittify themselves and all will work out splendid, you say? That sounds like magic. |
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| ▲ | porridgeraisin 3 days ago | parent | prev [-] | | They dont need to scale down anything. AGI is a red herring. Even Deepseek at its absurd prices is a very healthy business. Regarding their return on capex multiple, their CEO said they make a six-fold profit on their compute capex with 10 month recuperation. Because of this, all of them are spending aggressively on compute. Apart from that, user acquisition and data labelling are the major costs that are preventing net profitability right now. High quality data labelling is said to not have a cost advantage in china etc as well and they pay global market prices for this. I can confirm this is true in india too the model companies I know pay global market rates for high quality data. > Their costs are directly proportional to the amount of tokens the LLM produces. How is a monthly subscription plan supposed to account for such costs? By limiting the number of tokens you use per month? per week, per hour? And by limiting the inference time compute dedicated to each turn in each session. > need to recoup the world economy has shown itself capable of handling decade-scale recouping easily The main obstacle today in the inference business is the high variability in usefulness/token. This does not need to be solved, but rather only quantified. Innovation is needed to be able to reasonably bound this variance for a reasonable subset of tasks. And we are making progress on this. Naturally though, tasks on the frontier of current capabilities have very high variance. The last couple of years has followed the pattern where tasks no longer on the frontier have reduced variance, but I am not claiming this will continue to be the case generally as the frontier improves. | | |
| ▲ | lefty2 3 days ago | parent | next [-] | | > Even Deepseek at its absurd prices is a very healthy business. Regarding their return on capex multiple, their CEO said they make a six-fold profit on their compute capex with 10 month recuperation. That's "theoretical profit" - in some imaginary world where the free subscribers would pay the top tier cost. https://techcrunch.com/2025/03/01/deepseek-claims-theoretica... | | | |
| ▲ | rdedev 3 days ago | parent | prev [-] | | > their return on capex multiple, their CEO said they make a six-fold profit on their compute capex with 10 month recuperation I am not familiar with chineese model companies as much as I am with US based ones so I don't have much to say beyond that the CEO is incentivced to pump up those numbers. > By limiting the number of tokens you use per month? per week, per hour? And by limiting the inference time compute dedicated to each turn in each session. If this was so simple I don't know why GitHub copilot went to token based billing at my company. > This does not need to be solved, but rather only quantified. Innovation is needed to be able to reasonably bound this variance for a reasonable subset of tasks It's much better to make a business case for them after finding this bound right? Currently I can't use copilot for anything serious since I cannot predict how many credits one request is going to consume. Your point about non frontier tasks using less tokens makes sense. As you said, let's see if it holds up | | |
| ▲ | porridgeraisin 3 days ago | parent [-] | | Return on compute capex is tied mostly to gpu lifetimes so I don't think it will be different for the American companies, who also charge much more being closed source. > If this was so simple...copilot... Github copilot still has subscriptions. They moved away from request based accounting to token based accounting for the usage limits, as did cursor, and everybody else. |
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| ▲ | _aavaa_ 3 days ago | parent | prev [-] | | subsidized versus API pricing sure, but do we have concrete proof of how much it is subsidized versus the breakeven inference costs of those tokens? |
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| ▲ | intended 3 days ago | parent | prev | next [-] | | I remember the piracy era, and it used to be a joke whether anyone could actually stop it. Eventually MS dealt with piracy by going after firms, and finally by offering something cheap enough. Between the legal aspects, and the fact that its MS office, paying Rs 1800 a month is possible. I’ve been trawling every source I can find to understand what the story on the ground is, and when it comes to productivity it’s a huge mixed bag. The variance in outcomes between independent coders, frontier labs, someone in SV and someone in India is mind-bending right now. Most firms which talk about their AI plans are not seeing traction, and the AI projects are going to the same place that the ML projects used to go to die. It’s at the individual level that I am seeing productivity gains, however that isn’t something firms are happy to hear right now. | | |
| ▲ | stackskipton 3 days ago | parent [-] | | >Eventually MS dealt with piracy by going after firms, and finally by offering something cheap enough. Sure, because they realized that selling software at any cost because software has extremely low overhead. Selling 100M Windows at 2 USD was easier and my guess is a wash at that price. However, AI is not selling software, it's selling hardware usage which is not free and has real cost. If Rs 1800 which is 20 USD is not profitable, then they will not offer it. |
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| ▲ | thisisit 3 days ago | parent | prev [-] | | First I'd like to understand what are these "small" non-tech companies in tiny towns 45k to its employees? The last labor survey had average Indian salary pegged at 21k. > it pays for itself in literally a day Most comments in the thread say this but don't explain the how. How does it pay for itself "literally" in a day? Through productivity/time savings? How exactly? I can only assume people are talking about productivity gains. Have their been reports of increased productivity or layoffs in tiny town, small non-tech companies in India that I am unaware of? What is the source here? Without a concrete source this is mostly anecdotal evidence and not backed by data. Today there is novelty factor of AI. Questions or tasks which required people to really plan out now can be tested through AI quickly. To many people that seems like progress and that AI is paying itself. But most of it is busy work and isn't adding value to the companies. Given that everyone is on the AI hype train they might not be looking at the expenses closely. With time they will start poring it over and cancelling contracts en-masse. | | |
| ▲ | porridgeraisin 2 days ago | parent [-] | | > Don't explain the how They processed 10 cases in a day rather than 7. In some cases, new work took its place and the company makes a little bit more money, but this is a lagging effect naturally. > Have their been reports of increased productivity or layoffs in tiny town, small non-tech companies in India that I am unaware of PWC et al don't go around doing reports on these tiny companies bro. The only information you get is if you know people in that place and they tell you yourself, which is how I got to know. > Given that everyone is on the AI hype train they might not be looking at the expenses closely Yeah maybe F500 ceos exposed to LLM coding agents are on the hype train to some extent, but these M.S office pirating small companies are not on any hype train lol. > The last labor survey had average Indian salary pegged at 21k. Averaging across the whole of India gives you a useless number. In the richer regions, 21k is less than what a full time food delivery/quick commerce driver makes. | | |
| ▲ | thisisit 2 days ago | parent [-] | | > PWC et al don't go around doing reports on these tiny companies bro. The only information you get is if you know people in that place and they tell you yourself, which is how I got to know. I knew the post screamed "trust me bro" vibes and now I know for sure. Government does Labor force surveys. Here's one for last year. Point me out how the participation is changing through AI paying for itself.
https://www.pib.gov.in/PressReleasePage.aspx?PRID=2246009&re... > Averaging across the whole of India gives you a useless number. In the richer regions, 21k is less than what a full time food delivery/quick commerce driver makes. See the above survey for the figures. But then this is like someone using California to say how well America is doing. | | |
| ▲ | porridgeraisin 2 days ago | parent [-] | | > Government does Labor force surveys. I am very aware of MOSPI. We collaborate in compiling the data for them! BTW there is an MCP server now: https://github.com/nso-india/esankhyiki-mcp. What do you expect to glean out of PLFS though? Why would broad based labour force participation or other similar data change due to AI paying for itself? What? If you meant to somehow glean some information out of the wages report, note that the wages survey was last done in 25. The quarterly and monthly bulletins don't contain wage data. Regardless, these are too macro to give any sense of any change at all happening in AI-accelerable knowledge work. By "PWC report", I meant one where they went to firms and recorded using the same methodology some same notion of AI "paying for itself" or "increasing productivity". |
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| ▲ | alvdef 3 days ago | parent | prev | next [-] |
| anthropic and openai are a part of the ai economy, but not the only. the most valuable company in the world is nvidia, a massive player that benefits from the existance of the ow models. what im trying to say is that we focus a bit too much on the labs, but the biggest part is in the infra that makes everything possible. |
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| ▲ | red-iron-pine 2 days ago | parent | prev | next [-] |
| bingo. it helped me sort through 2 CSVs earlier today. grunt work, really, and nothing some python skills or excel-fu couldn't solve just as quickly. it also got something wrong, and I had to put it into a different AI to understand why. not really to bad though, a 2 minute, sanity check. I'd pay no more than, say $3 for the use, maybe 5. If they want to start clocking us $200 a day, or $4000 a license or whatever -- nah. |
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| ▲ | carlosjobim 3 days ago | parent | prev | next [-] |
| > But the question is how much are people willing to pay for AI. That depends on how much more money they can make with AI or save with AI. It shouldn't be very hard to know that number in a well run business. Even for a one man business. |
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| ▲ | surajrmal 2 days ago | parent | prev | next [-] |
| If they can get productivity increases equivalent to .1% it pays for itself. That's roughly equivalent to firing 1 in 1000 employees to finance the software. |
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| ▲ | braebo 3 days ago | parent | prev | next [-] |
| I pay the 200 max for Fable daily driving and it’s worth every penny |
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| ▲ | r0b05 3 days ago | parent | prev | next [-] |
| Won't the Chinese providers have to raise their prices as well due to the economics of serving inference at scale? |
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| ▲ | aurareturn 2 days ago | parent | next [-] | | Yes. People keep thinking that Chinese models are free or near free for some reason. In reality, they're raising prices too. I was looking at Kimi K3 prices on OpenRouter and it's nearly the same as Anthropic and OpenAI. | |
| ▲ | spwa4 3 days ago | parent | prev [-] | | Buy an M5 max for $4k and you have a portable Deepseek 0731 for life. | | |
| ▲ | dexterdog 3 days ago | parent | next [-] | | But it won't last for life. It will probably last about 4 years so that equates to about 100/mo. | | |
| ▲ | spwa4 3 days ago | parent [-] | | M1 is finishing it's 6th year of life and going strong ... | | |
| ▲ | dexterdog 3 days ago | parent [-] | | Have you been trashing the non-replaceabe SSD with constant AI workloads? Do you have any idea how much electricity it uses over it those 4 years? | | |
| ▲ | pulse7 3 days ago | parent | next [-] | | You cannot wear out an SSD through AI inference alone. LLM weights are only read from the SSD, and read operations do not contribute to SSD wear. SSD wear is primarily caused by write and erase operations. | |
| ▲ | kadoban 2 days ago | parent | prev [-] | | > Have you been trashing the non-replaceabe SSD with constant AI workloads? Your other point is valid, but you're either vastly underestimating how many reads/writes a modern SSD can take or vastly overestimating how much output a typical LLM is capable of. |
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| ▲ | whateveracct 2 days ago | parent | prev [-] | | models are stuck in time. eventually the world moves forward and it is trained on too much obsolete data. training cannot end for LLMs intrinsically. it's not some fixed cost. it's an ongoing one. | | |
| ▲ | jurgenburgen 2 days ago | parent [-] | | > eventually the world moves forward and it is trained on too much obsolete data. This is why LLMs are never going to be AGI. Humans don’t become obsolete just because they age. | | |
| ▲ | saghm 2 days ago | parent [-] | | Humans do die eventually though, which is an even more severe form of obsolescense. I don't think they'll be AGI either, but that argument doesn't seem super compelling. | | |
| ▲ | spwa4 2 days ago | parent [-] | | On the other hand you have the old saying "science advances one funeral at a time", indicating death solves at least as many problems as it causes. (the point being that old, powerful professors have more than once blocked progress in their fields for decades. And only a funeral, eventually, solves the problem ...) |
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| ▲ | fuzzfactor 3 days ago | parent | prev | next [-] |
| >I'm sure there will be some losers, This is the way it is on Wall Street more each century, and for AI to go public on that exchange it's going to have to go big or go home. Considering the amount of money that has already been spent privately. There is no alternative pipeline to replenish those reserves, and different people have different ideas about capacity and bottlenecks relative to ambitions and what they are supposed to get for their money. As has been mentioned in another comment, there is no alternative foundation other than optimism either. The exchange wouln't exist if it weren't originally intended to trade only shares that were all worth holding otherwise. Naturally some worth holding more than others. This is so big it will be necessary to be able to fool way more people with way more money than usual, otherwise those that prevail will have nowhere near their wildest dreams come true. Naturally AI is never going to fly off the shelf like it could until it starts getting cheaper all the time for huge jumps in performance. Cheap home computers will need to be able to do quite a bit more than they can only do today while connected to a massive AI data center, without ever having been connected to anything outside the home at all. Otherwise AI can not ever be considered "general" any more than computing could be considered personal, until you were no longer reliant on a remote mainframe in a huge out-of-state data center somewhere tied by a thread leading through a squeaky modem over monopolized communication lines. This differential between clunky (clanky?) old data centers' overall computing power relative to the amount held freely within homes & businesses is something that looks like it could be regaining exploitability like never in decades. I know one day Woz jumped right in without needing to be a greedy businessman because there was no possible downside, and he could let just about any dedicated growth leader make as much money as they wanted off his technology. Plus Jobs was no slouch in many ways and Woz never needed to worry with a product that sells itself to begin with, putting Jobs in hog heaven where he could persuasively bring it to the next level almost whenever he wanted like you can do few other ways. So not just dot-com related hardware & software. That goes for memory and storage too, people should do the math on how affordable nominal amounts are supposed to be by now. If everything were still normal 16GB of DDR4 would be about $10, at least by 2027, so it hasn't merely doubled in the last year which is the most obvious part, it has skyrocketed to 10x what it would have been. And still rising not falling, so all this is going to have to be reversed for consumers to even afford what they used to be able to do. For people who didn't want to spend a thing on AI until it's naturally way more capable and constantly getting cheaper like it should be, it's pretty frustrating when it's already been unavoidably costing "indirectly" more than they have been willing to pay if they were getting maximum benefit, when most of them have only gotten more surveillance. One day "indirectly" was just no longer true through no fault of millions of people. And growing as fast as the money stream will allow. Up until recently AI was way more niche and fewer ordinary consumers were exposed, where now there are millions more aware of its influence and growing fast. But the more aware more ordinary people become, millions more opinions are going to come to the surface and need to be dealt with. >whale economy. Thar she blows! One pervasive opinion is that so far it's made by rich people for rich people, and more so than most those who want to get rich quick are joining the bandwagon. Of course what consumers see in the media is only the "band directors" who are already rich to begin with, they set the example because they now want to get richer quicker and this is the vehicle they have chosen to do that. This is not unexpected, after all they always get what they want when it's things you have to be ungodly rich to do. This makes for company valuations based more on optimism than anything else and once that has eclipsed underlying worth then any unforeseen bottlenecks or financing stumbles become highly magnified. For one thing there may not be enough momentum to even fully build enough data centers to fulfill some players' plans for recouping such large investments, but at the same time AI's not going to really get good until data centers are not needed at all, which is so ominous there appears to be even more force being applied to encourage people to ignore things like this. Otherwise it could get too shocking. This disparity in upside just plain instinctively sidelines more ordinary people as it builds, so the number of people who are just going to have to wait for AI and everything associated with it to start getting cheaper all the time becomes a force in itself. It'll be easy to notice without being a finance guru. Until then gamble at your own risk :\ |
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| ▲ | surgical_fire 3 days ago | parent | prev | next [-] |
| Rofl, I already went for cheaper Chinese solutions. I can achieve more than I could when I was giving OpenAI 20 bucks a month, and for a fraction of the price. I have no idea why people still use ChatGPT or Claude. |
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| ▲ | coliveira 3 days ago | parent | next [-] | | Most people don't understand how cheap models like DeepSeek and similar are. I have $5 in an account that I use for months. I can get very complex code for less than 50 cents. | |
| ▲ | Kuyawa 3 days ago | parent | prev [-] | | Me too. Sinophobia may be the culprit, too many years watching fox or cnn is my guess? I love chinese phones, cars, cities, people, and now AI models. There is a beautiful world out there to admire if people is willing to open their eyes. |
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| ▲ | rdedev 3 days ago | parent | prev | next [-] |
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| ▲ | phyalow 3 days ago | parent | prev | next [-] |
| I spent $18k in credits last month, I have 3x 20x Anthropic accounts (for Fable to bypass limits) which runs me another $600ish p/m and then a chatgpt pro account another $200 p/m. The value I got out of it is easily 1-200x what I paid. |
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| ▲ | kamranjon 3 days ago | parent | next [-] | | 1 to 200 is a pretty big spread to between losing 18k dollars and making 3.6 milllion - do you have any actual numbers on the value produced from this 18k investment? | |
| ▲ | treis 3 days ago | parent | prev | next [-] | | You make ~2 million dollars a month? | | | |
| ▲ | intended 3 days ago | parent | prev | next [-] | | Examples like this come up as sub comments very often, but they don’t address the point. Most people will not go beyond $20, forget a 18k. | | |
| ▲ | zippyman55 3 days ago | parent | next [-] | | I use AI daily and pay zero dollars. I get my work done and I stay sharp.
A huge mass will always choose the cheapest option. | | |
| ▲ | intended 3 days ago | parent [-] | | Absolutely! The opposite end of the preference scale from someone willing to spend 18k a month. |
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| ▲ | etempleton 2 days ago | parent | prev [-] | | Most people won’t go beyond free. A lot of people will spend $20 and some will go above $50. |
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| ▲ | CrosswordPuzzle 3 days ago | parent | prev | next [-] | | What are you using it for? I have to assume some kind of agentic workload. Also curious to know when (if ever) you would pivot to Chinese providers to save $$$ | |
| ▲ | ofjcihen 3 days ago | parent | prev [-] | | Honestly with that kind of usage how do you even know what you’re delivering? |
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| ▲ | johnbarron 3 days ago | parent | prev [-] |
| You can now, as of this week, run locally models with the same performance of a SOTA model of March this year: https://news.ycombinator.com/item?id=49214008
https://news.ycombinator.com/item?id=49229621 The FAFO day of Anthropic and OpenAI arrived. |
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| ▲ | Aurornis 3 days ago | parent | next [-] | | You will spend thousands of dollars on hardware to run those at lower quality (quantized) than the benchmarks where they match March SOTA performance. Source: I have the hardware to run those locally. I would never recommend it to anyone trying to save money. It’s so much cheaper to pay even Anthropic or OpenAI. | |
| ▲ | IncreasePosts 3 days ago | parent | prev [-] | | Not many people have $10k of specific hardware lying around |
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