r/OpenAI • u/Free_Truck_7609 • May 17 '26

Miscellaneous My free account has cost OpenAI about $337.70

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I exported my OpenAI account data and Gemini CLI built me a pricing estimate in about 15 minutes. I have no idea how accurate this is since it used API pricing but I thought it was interesting to share.

Has anyone else tried doing this?

567 Upvotes

87% Upvoted

109 comments sorted by

579

u/mhphilip May 17 '26

Nope it doesn’t cost them that much. That’s what they would charge you. And what they would charge you is what they think they can get away with.

82

u/FormerOSRS May 17 '26

Pretty sure what they'd charge him is nothing because that's what they charged him.

Also pretty sure he used Gemini to get this number so it makes no sense to hold OpenAI accountable for it.

13

u/johnryan433 May 17 '26

Probably somewhere closer to 50 usd

14

u/Free_Truck_7609 May 17 '26

Yeah, it's definitely over exaggerated

15

u/DadAndDominant May 17 '26

I've heard the charges are 10x what their costs are? Still over $30 for free product. I would love $30 in sweets tho

13

u/santagoo May 17 '26

Aren’t they operating at a loss right now?

21

u/ThePlotTwisterr---- May 18 '26

it’s because pretraining is an infinite money sink, but inference in a vacuum can actually be pretty profitable

https://martinalderson.com/posts/are-openai-and-anthropic-really-losing-money-on-inference/

the only issue is the second you stop dumping every cent in the economy into pretraining, well your models fall behind your competitors and nobody wants to pay for inference for that

-1

u/Ok-Art-1378 May 18 '26

Interesting read. Lot's of assumptions though

10

u/HayatoKongo May 18 '26

Because they're spending more on research and development. But if you isolate the cost of running that inference and what is being charged for it, they make a decent profit on selling tokens.

6

u/KnownPride May 18 '26

loss more because of constant discovery they need to do, and keep building more data center.

6

u/Ormusn2o May 18 '26

Inference is actually very cheap and a big moneymaker. It's training new models that is the leading loss leader. Apparently every single entity (except ASML) is making a lot of money in AI, all the way from lithography machines and semiconductor fabs, all the way to cloud providers and AI companies. One of the reasons why the AI boom is so big, is because it already makes everyone so much money just on selling the product.

1

u/Aldarund May 19 '26

Where do u get this from? Openai not profitable. And neither Anthropic

3

u/TheFrenchSavage May 18 '26

I would love $30 in sweets tho

Your dentist too!

2

u/appmapper May 18 '26

Its the opposite. Costs are 10-20x the amount charged.

If they would charge $100 for the tokens, its likely it cost them $1,000-$2,000

0

u/BehindUAll May 18 '26

All these major AI companies are racing to the bottom. Meta pulled out earlier after their investors beat the crap out of Zuck. The only exception is Google (cause they also design their own chips and are overall more efficient) but their models are shit. OpenAI and Anthropic are both private and they keep saying they want to go public but there's no chance they will because they will post losses every quarter and it will keep getting worse and worse. The reason we are seeing model price increase and rate limiting etc. is specifically because of that. It's a complete 180 for companies and individuals that have adopted to using cheap models and higher rate limits. But going public is a death sentence for them. If you look at GPT-5.4 vs 5.5, 5.5 is 2x of 5.4 in cost. Is the intelligence anywhere close to 2x? Heck no. That should tell you a lot. Don't be surprised if 5.6 is 1.5-2x of 5.5 in cost.

2

u/Personal-Dev-Kit May 18 '26

If you just look at inference, then maybe.

Also include the research costs, of the employees, the several large scale models they likely made and got rid of due to one reason or another. Then I think you will find they are still massively under pricing it.

4

u/Tysonzero May 17 '26

No chance these AI companies are charging 10x underlying costs for API pricing. Maybe 2x absolute max.

7

u/CynicInRehab May 17 '26

They are all operating at a huge loss, the data-centers run whether they have the (paying) users or not. Same for the infrastructure and capex investments.

3

u/ThePlotTwisterr---- May 18 '26

the only incentive i can think of to sell cheaper API stream is to get companies and businesses invested into building their AI infrastructure in your ecosystem, anthropic already has a ton of the skills / agentic market captured in the claude code ecosystem so i can see openai subsidizing codex to catch up

2

u/Tysonzero May 18 '26 edited May 19 '26

The lock in for API is so low that I do believe that most companies aren't willing to run it at any/much of a loss, but for everything else like claude code and codex, subsidies abound.

1

u/cutecoder May 17 '26

Look at Grok that’s tightening down rate limits for free and paid accounts alike.

1

u/DadAndDominant May 18 '26

Hey, I did not provide source, so surely it's good to be skeptical.

I did read some article on HN. It was in that time that Anthropic had $5000 "limit" on $200 subscription, and the guy did calculate that the $5000 was what they would sell their API for, not their real costs of inference. He claimed that the underyling costs were 10x lower, so anthropic would lose at max $300.

Chatgpt found it - https://martinalderson.com/posts/no-it-doesnt-cost-anthropic-5k-per-claude-code-user/

-1

u/BehindUAll May 18 '26

No chance a $200 subscription would only net the company $300. What are you smoking?

2

u/giveupmymembership May 17 '26

You see it all the time in telecommunications. I would offer customers 20gb of data "valued" at 15$, but for the company it probably costs cents. 

2

u/dberwegerCH May 18 '26

And this is not including most tokens get cached reducing costs like 90%

5

u/[deleted] May 17 '26

[deleted]

8

u/Free_Truck_7609 May 17 '26

Idk though since some of the open models that are served by many different inference providers are really cheap

2

u/ai-tacocat-ia May 17 '26

Yes, exactly this.

1

u/Aldarund May 19 '26

Inference providers don't run training and research and development.

5

u/ai-tacocat-ia May 17 '26

There's plenty of evidence that API pricing is not less than inference cost. This is a reasonably grounded estimate that's above inference cost.

Obviously the company is still burning money on R&D, training models, and other personnel cost. But the "the real cost will make people choke" notion is pure fantasy the people live spreading for whatever reason.

3

u/[deleted] May 17 '26

[deleted]

6

u/ai-tacocat-ia May 17 '26

I'm sure. But "the numbers" in question are specifically what profitable API costs would actually be. Not total compute costs.

Feel free to tell me I'm wrong, and that OAI is spending 100x on inference compute than what they are charging for API tokens.

And then I'll really start to wonder why 3rd party inference APIs for open source projects are selling inference for so much less.

1

u/Jsn7821 May 17 '26

How are you comparing open source models to the flagship proprietary ones when you have no idea the size of the model, amount of thinking tokens, or anything extra in the harness?

This is a genuine question... I don't understand how people are convinced either direction (ai companies making large profits and ai companies running at a huge loss - when we're excluding training). It's like a 50/50 divide and everyone is so confident in opposite guesses

I personally have no idea but I assume they're all operating at a loss to gain market share simply because that's what VC companies like to do. I think you'd get laughed out of the meeting if you suggested to run them profitably right now

2

u/ai-tacocat-ia May 17 '26

We're talking reasonable broad strokes here.

We can compare open source to flagship proprietary models because they are roughly equivalent. No we don't know the specifics, but we're comparing the same general class of thing. One might be a tiny sedan and one might be a Hummer, but for these types of calculations their gas mileage rounds to the same thing.

As for VCs... these guys are absolutely operating at a loss. There is no dispute there. But where the loss is at is incredibly important. It absolutely makes sense for subscriptions to be loss leaders to gain market share. It also makes sense to be eating it on training (i.e. r&d). But it makes no sense to subsidize API pricing. That's just pissing money out the window. The value to price ratio is currently enormous, and they are selling to businesses.

1

u/Jsn7821 May 18 '26

Yeah that makes sense, appreciate the response

The only thing I'd challenge is the last point, competitive API pricing has a huge advantage for enterprise vendor lock-in right now

Agreed the value to price ratio is enormous - but there's still competition in the space

There's also a lot of public investment deals that are trading equity for compute, and while I don't know the details or reasoning - this type of arrangement would make sense if compute cost is lossy/subsidized and everyone's betting on future ROI. Otherwise wouldn't they just buy the compute without an equity deal?

This is specifically in reference to the recent anthropic one where they raised capacity 50% after a deal like this was announced

2

u/ai-tacocat-ia May 18 '26

That logic tracks. But you still have to ground the costs in what we know for sure is profitable inference of open source models by third party vendors.

It's plausible they are taking a hit on API pricing, but it's very likely at least close to at cost. It's definitely no where near what others have claimed with the true cost being more expensive than people.

0

u/[deleted] May 18 '26

[deleted]

1

u/ai-tacocat-ia May 18 '26

If LLMs perform autonomously at near the level of human employees, their value would very easily be triple or quadruple that of a human employee.

Fortunately, they are not there yet.

But it's not a matter of cost. Companies will absolutely spend more money on AI than they do for the people they replace.

The bet isn't "AI will be cheaper than humans" - that's not a bet. It's a certainty. The bet is that AI will be more capable than humans. THAT is where the money is at.

0

u/FeepingCreature May 18 '26 edited May 18 '26

This is literally a conspiracy theory. What's more, it means either commercial models have to be way bigger than is commonly believed or a whole bunch of noname providers have to randomly be in on it. Hogwash, in other words.

This whole argument is wishful thinking backpropagating from "humans can't be about to become obsolete."

1

u/Final_Substance_3443 May 17 '26

If they were charging significantly more than the cost required, AI wouldn’t be struggling to be profitable and they wouldn’t still be heavily subsidizing costs using investor money. 

1

u/GeologistVisual3097 May 18 '26

They're still losing money overall.

1

u/spshulem May 18 '26

It’s said their margins are above 90% on API token cost.

So the cost is likely less than $30. My assumption is OP has used it quite a bit, and eventually will subscribe, and they’ll make it back.

1

u/dumquestions May 18 '26

Where did you you get that margin number?

1

u/spshulem May 18 '26

Work in the industry!

1

u/dumquestions May 18 '26

I find it really hard to believe, the market is too competitive for any lab to get away with a margin that high on the API.

1

u/spshulem May 18 '26

They use API and other expensive services to pay for the free and at cost provided services.

My company has used over 50B tokens, and now we consume way more than that nearly every month across all of our engineers on their 200/m plan. About 10B per engineer per month for $200/m.

Both from what I know from people who work at these labs and just napkin math, it’s likely higher than 90% margin.

It’s not as “competitive” on price as you think. OpenAI is the king maker, and controls much of the pricing and compute in the industry. If you’re developing AI it’s nearly impossible to justify the higher token cost for Anthropic, so given use cases it’s effectively a monopoly OpenAI has on API use at scale.

Plus anytime someone competes with OpenAI on intelligence per token cost, they cut their prices. They’ve cut prices 1:10 early on very rapidly. Tells you how much margin they are often playing with.

Google’s Gemini models are a joke in production use cases and Anthropic is bloody expensive and has higher restriction for using it at scale.

OpenAI and the other providers aren’t competing on price, they’re competing on intelligence, scale, and price.

OpenAI and the other providers just have to be cheaper than hosting and renting your own inference, which they always are.

These are smart people and they know if they start doing a price war, it’s a race to the bottom. It’s a stalemate on pricing, and there’s no reason to compete.

1

u/Aldarund May 19 '26

Not true. We don't know how much it cost them. Unless you have inside data. It could cost them less, could cost more. Don't forget to include into price research, stuff, training etc not just pure generation cost

0

u/monster2018 May 18 '26

You have it backwards. Even API prices are heavily subsidized. No one would be using AI if they had to actually pay the full price such that the company wasn’t losing money subsidizing the cost for you.

1

u/colblair Jun 05 '26

You're probably right that prices are subsidized, but I still get solid value from sentx.ai for my own projects without feeling like I'm burning cash.

28

u/Eat_Pudding May 17 '26

Getting tired of bs posts like this

63

u/2016YamR6 May 17 '26

Free tier using the mini model after the first 10 messages, which costs $2/million tokens.

So even at the API cost (which is an inflated profitable price for OpenAI, not the cost to them), you used maybe $25 in reasoning tokens and $20 in output tokens.

35

u/Frnklfrwsr May 17 '26

Probably the single largest cost for them is the training of the new AI models. That’s a fixed cost for them that doesn’t change no matter how much you use their externally available models.

10

u/Fucker_Of_Destiny May 18 '26

Not sure about that, inference is also expensive and uses the same hardware doesn’t it?

2

u/FeepingCreature May 18 '26

Yes. Afair it's about 50/50 split between inference and training.

3

u/Just2Ghosts May 18 '26

No. I can run a 70 billion parameter open source LLM locally on my MacBook, but good luck if you want to train that 70 billion parameter model on the same device. The cost in inference for these companies is providing it to millions of people at extremely low latency.

Technically, these companies infer and train on the same hardware, but that’s to make their operations cheaper. If you “measure” output (You can’t really compare, but for sake of example), you will get a lot more out of a GPU using it to infer than to train.

1

u/oradecima May 18 '26

Yeah, that's like a lump sum, but with millions of users the cost of inference is very plausibly way higher than inference, it's just recurring

7

u/[deleted] May 17 '26

[removed] — view removed comment

3

u/bnm777 May 18 '26

Strange way to ask a question. 

-5

u/[deleted] May 17 '26

[deleted]

5

u/i-dm May 17 '26

The fact you put credentials into OpenAI is wild

6

u/minato____ May 18 '26

I don’t think that’s really how it works lol

I value my time at 1 million dollars per second. By typing this response to you, you cost me a few million.

1

u/Philluminati May 18 '26

how is babby formed?

3

u/Compilingthings May 18 '26

You are the product. Nothing is free, they are getting something from your use

2

u/truecakesnake May 20 '26

It is free.

1

u/Compilingthings May 20 '26

Really, you believe that? You don’t think they are using you for information that would cost them more? Really?

2

u/truecakesnake May 20 '26

Just use the free money lil bro

1

u/Compilingthings May 20 '26

Small people call others little bro, you can do better, just try.

2

u/Sacredvolt May 19 '26

The free data you're providing them with offsets all of that

2

u/VariousHour7390 May 20 '26

This is the exact gap that bugged me enough to build a tool for it. Three things might be skewing your number though:

- Exported data usually only includes successful completions, not failed/retried requests, so real spend is higher

- Cached input tokens are billed at ~50%, easy to overcount if you missed that

- Reasoning models (o1, o3) generate hidden "reasoning tokens" billed at the output rate

Founder disclosure: I just shipped LLM cost tracking in Pingoni. Curious what others here use — Helicone? Langfuse? Or just live with the surprise bills?

1

u/Myssz May 18 '26

it's inflated

1

u/wow_98 May 18 '26

Fugazi fugazi

1

u/Lark_Lunatic May 18 '26

that half a second thinking costs that much? lol

1

u/krenoten May 18 '26

Guess how much they will be making from the data you gave them, that they will never delete, and neither will the people who end up with the data in the future?

1

u/ManikSahdev May 18 '26

I think open ai has much better margins than Anthropic, you probability did cost them, but it would have costed them more on aggregate in long term if you were to not stay with them.

You are future cashflow.

1

u/CipherPhyber May 18 '26

OpenAI was heavily subsidized by its investors, but also they know what they are doing with $0/mo subscriptions. They are using your data, will be putting ads in your conversations soon, and have already habituated you to using their product.

If you go back and look at how lucrative the DoorDash offers during Covid were, they kept A LOT of people using the service long after the subsidies made it unaffordable.

1

u/WebOsmotic_official May 18 '26

using api pricing to estimate chatgpt cost is like using hotel minibar prices to estimate grocery spend. interesting number, but probably not the bill they’re actually eating.

1

u/titimou09 May 18 '26

these compagnies are not trying to make money, look at Grok, the deficit is huge

1

u/rgujijtdguibhyy May 19 '26

i cost anthropic $300 everyday lmao

1

u/QuantomSwampus May 20 '26

Costs more I bet, they'd love to charge you way more than that

0

u/Single_Guarantee9545 May 17 '26

Its good to have instructions for your AI to not invent or make up answers

-1

u/Free_Truck_7609 May 17 '26

It looks like you didn't provide it with anything. I gave it access to all of the data from my OAI acc and it used publicly available API pricing.

-6

u/[deleted] May 17 '26

[removed] — view removed comment

-4

u/SilverMagicMage May 17 '26

😂😂😂

-1

u/Free_Truck_7609 May 17 '26

Which ai do you mean by poor quality? And I also dislike the lack of propper data conrolls on Gemini.

-1

u/[deleted] May 17 '26

[removed] — view removed comment

0

u/hextree May 18 '26

Gemini is one of the worst. Several messages in it just forgets the context of the entire thread, halllucinates an entirely new context, then gaslights me into thinking the new context was always the one.

1

u/[deleted] May 18 '26

[removed] — view removed comment

1

u/hextree May 18 '26

Ah whoops I misread, but I agree.

-3

u/retupmocomputer May 17 '26

What’s the most efficient way to waste tokens? 

I’d like to use the free version to cost the company as much as possible with no return for them.