[HN Gopher] OpenAI's H1 2025: $4.3B in income, $13.5B in loss
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OpenAI's H1 2025: $4.3B in income, $13.5B in loss
Author : breadsniffer
Score : 188 points
Date : 2025-10-02 18:37 UTC (4 hours ago)
(HTM) web link (www.techinasia.com)
(TXT) w3m dump (www.techinasia.com)
| koolba wrote:
| " _We lose money on every sale, but make it up in volume!_ "
| NooneAtAll3 wrote:
| > US$2.5 billion on stock-based compensation
|
| um...
| chevman wrote:
| Never having worked for a company in a position like OpenAI,
| how does this manifest in the real world as actual comp?
|
| Like I get 50,000 shares deposited in to my Fidelity account,
| worth $2 each, but i can't sell them or do anything with them?
| xuki wrote:
| It's just an entry on some computer. Maybe you can sell it on
| a secondary market, maybe you can't. You have to wait for an
| exit event - being acquired by someone else, or an IPO.
| changoplatanero wrote:
| You got the right idea there. They wouldn't actually show up
| in your Fidelity account but there would be a different
| website where you can log in and see your shares. You
| wouldn't be able to sell them or transfer them anywhere
| unless the company arranges a sale and invites you to
| participate in it.
| antognini wrote:
| I can't speak to OpenAI's specific setup, but a lot of
| startups will use a third party service like Carta to manage
| their cap table. So there's a website, you have an account,
| you can log in and it tells you that you have a grant of X
| shares that vests over Y months. You have to sign a form to
| accept the grant. There might be some option to do an 83b
| election if you have stock options rather than RSUs. But
| that's about it.
| zzbzq wrote:
| In my experience owning private stock, you basically own part
| of a pool. (Hopefully the exact same classes of shares as the
| board has or else it's a scam.) The board controls the pool,
| and whenever they do dividends or transfer ownership, each
| person's share is affected proportionally. You can petition
| the board to buy back your shares or transfer them to another
| shareholder but that's probably unusual for a rank-and-file
| employee.
|
| The shares are valued by an accounting firm auditor of some
| type. This determines the basis value if you're paying taxes
| up-front. After that the tax situation should be the same as
| getting publicly traded options/shares, there's some choices
| in how you want to handle the taxes but generally you file a
| special tax form at the year of grant.
| sharadov wrote:
| You can sell your vested options before IPO to Forge Global
| or Equity Bee.
| JCM9 wrote:
| Until there's real liquidity (right now there's not) it's
| just a line item on some system you can log into saying you
| have X number of shares.
|
| For all practical purposes it's worth nothing until there is
| a liquid market. Given current financials, and preferred cap
| table terms for those investing cash, shares the average
| employee has likely aren't worth much or maybe even anything
| at the moment.
| elamje wrote:
| this hides major dilution until future financings
|
| best to treat it like an expense from the perspective of
| shareholders
| hmate9 wrote:
| $2.5B in stock comp for about 3,000 employees. that's roughly
| $830k per person in just six months. Almost 60% of their revenue
| went straight back to staff.
| tomasphan wrote:
| That's how it should be, spread the wealth.
| onlyrealcuzzo wrote:
| Spreading illiquid wealth *
| BhavdeepSethi wrote:
| Funny since they have a tender offer that hits their
| accounts on Oct 7.
| gk1 wrote:
| They've had multiple secondary sales opportunities in the
| past few years, always at a higher valuation. By this
| point, if someone who's been there >2 years hasn't taken
| money off the table it's most likely their decision.
|
| I don't work there but know several early folks and I'm
| absolutely thrilled for them.
| chermi wrote:
| Secondaries open to all shareholds are on upward trend
| across start-ups. I think it's a fantastic trend.
| Der_Einzige wrote:
| Oh no, "greedy" AI researchers defrauding way greedier VCs
| and billionaires!
| yieldcrv wrote:
| private secondary markets are pretty liquid for momentum
| tech companies, there is an entire cottage industry of
| people making trusts to circumvent any transfer
| restrictions
|
| employees are very liquid if they want to be, or wait a
| year for the next 10x in valuation
| onlyrealcuzzo wrote:
| Oh, yes, next year OpenAI will be worth $5T, sure
| hlava wrote:
| To the top 1%.
| Hamuko wrote:
| It doesn't seem _that_ spread out.
| kibwen wrote:
| Sounds like they could improve that bottom line by firing all
| their staff and replacing them with AI. Maybe they can get a
| bulk discount on Claude?
| darth_avocado wrote:
| They have to compete with Zuckerberg throwing $100M comps to
| poach people. I think $830k per person is nothing in
| comparison.
| munk-a wrote:
| Both numbers are entirely ludicrous - highly skilled people
| are certainly quite valuable. But it's insane that these
| companies aren't just training up more internally. The 50x
| developer is a pervasive myth in our industry and it's one
| that needs to be put to rest.
| bitexploder wrote:
| The 50x distinguished engineer is real though. Companies
| and fortunes are won and lost on strategic decisions.
| charcircuit wrote:
| It's not a myth and with how much productivity AI tools can
| give others, there can be an order of magnitude difference
| than outside of AI.
| xnx wrote:
| > training up more internally
|
| Why would employees stay after getting trained if they have
| a better offer?
| coolspot wrote:
| A tamper-proof electronic collar with some C4.
| munk-a wrote:
| They won't always. You'll always have turn-over - but if
| it's a major problem for your company it's clearly
| something you need to work out internally. People,
| generally, hate switching jobs, especially in an
| uncertain political climate, especially when expenses are
| going up - there is a lot of momentum to just stay where
| you are.
|
| You may lose a few employees to poaching, sure - but the
| math on the relative cost to hire someone for 100m vs.
| training a bunch employees and losing a portion of those
| is pretty strongly in your favor.
| hadlock wrote:
| You have to out-pay to keep your talent from walking out
| the door. California does not have non-competes. With the
| number of AI startups in SF you don't need to relocate or
| even change your bus route in most cases.
| darth_avocado wrote:
| This. The main reason OpenAI throws money at top level
| folks is because they can quickly replicate what they
| have at OpenAI elsewhere. Imagine you have a top level
| researcher who's developed some techniques over multiple
| years that the competition doesn't have. The same
| engineer can take them to another company and bring
| parity within months. And that's on top of the progress
| slowing down within your company. I can't steal IP, but
| but sure as hell can bring my head everywhere.
| xur17 wrote:
| If it's an all out race between the different AI providers,
| then it's logical for OpenAI to hire employees that are
| pre-trained rather than training up more internally.
| lovecg wrote:
| Do other professionals (lawyers, finance etc.) argue for
| reducing their own compensation with the same fervor that
| software engineers like to do? The market is great for us,
| let's enjoy it while it lasts. The alternative is all those
| CEOs colluding and pushing the wages down, why is that any
| better?
| a4isms wrote:
| > The 50x developer is a pervasive myth in our industry
|
| Doesn't it depend upon how you measure the 50x? If hiring
| five name-brand AI researchers gets you a billion dollars
| in funding, they're probably each worth 1,000x what I'm
| worth to the business.
| gmerc wrote:
| Zuck decided it's cheaper than building another Llama
| __turbobrew__ wrote:
| The [?]x engineer exists in my opinion. There are some
| things that can only be executed by a few people that no
| body else could execute. Like you could throw 10000
| engineers at a problem and they might not be able to solve
| that problem, but a single other person could solve that
| problem.
|
| I have known several people who have went to OAI and I
| would firmly say they are 10x engineers, but they are just
| doing general infra stuff that all large tech companies
| have to do, so I wouldn't say they are solving problems
| that only they can solve and nobody else.
| remus wrote:
| I think you're right to an extent (it's probably fair to
| say e.g. Einstein and Euler advanced their fields in ways
| others at the time are unlikely to have done), but I
| think it's much easier to work out who these people are
| after the fact whereas if you're dishing out a monster
| package you're effectively betting that you've found
| someone who's going to have this massive impact before
| they've done it. Perhaps a gamble you're willing to take,
| but a pretty big gamble nonetheless.
| scottyah wrote:
| It's apparent in other fields too. Reminds me of when
| Kanye wanted a song like "Sexy Back", so he made Stronger
| but it sounded "too muddy". He had a bunch of famous,
| great producers try to help but in the end caved and
| hired the producer of "Sexy Back". Kanye said it was
| fixed in five minutes.
|
| Nobody wants to hear that one dev can be 50x better, but
| it's obvious that everyone has their own strengths and
| weaknesses and not every mind is replaceable.
| causalmodels wrote:
| These numbers aren't that crazy when contextualized with
| the capex spend. One hundred million is nothing compared to
| a six hundred billion dollar data center buildout.
|
| Besides, people are actively being trained up. Some labs
| are just extending offers to people who score very highly
| on their conscription IQ tests.
| datadrivenangel wrote:
| if Meta is throwing 10s of million at hot AI staffers, than
| 1.6M average stock comp starts looking less insane, a lot of
| that may also have been promised at a lower valuation given how
| wild OpenAI's valuation is.
| varenc wrote:
| It's a bit misleading to frame stock comp as "60% of revenue"
| since their expenses are way larger than their revenue. R&D was
| $6.7B which would be 156% of revenue by the same math.
|
| A better way to look at it is they had about $12.1B in
| expenses. Stock was $2.5B, or roughly 21% of total costs.
| skybrian wrote:
| It's not cashflow, though, and it's not really stock yet, I
| don't think? They haven't yet reorganized away from being a
| nonprofit.
|
| If all goes well, someday it will dilute earnings.
| gizajob wrote:
| I'm guessing it will be a very very skewed pyramid rather than
| equal distribution.
| manquer wrote:
| Stock compensation is not cash out, it just dilutes the other
| shareholders, so current cash flow should not have anything do
| to the amount of stock issued[1]
|
| While there is some flexibility in how options are issued and
| accounted for (see FASB - FAS 123), typically industry uses
| something like a 4 year vesting with 1 year cliffs.
|
| Every accounting firm and company is different, most would
| normally account for it for entire period upfront the value
| could change when it is vests, and exercised.
|
| So even if you want to compare it to revenue, then it should be
| bare minimum with the revenue generated during the entire
| period say 4 years plus the valuation of the IP created during
| the tenure of the options.
|
| ---
|
| [1] Unless the company starts buying back options/stock from
| employees from its cash reserves, then it is different.
|
| Even secondary sales that OpenAI is being reported to be
| facilitating for staff worth $6.6Billion has no bearing on its
| own financials directly, i.e. one third party(new investor) is
| buying from another third party(employee), company is only
| facilitating the sales for morale, retention and other HR
| reasons.
|
| There is secondary impact, as in theory that could be shares
| the company is selling directly to new investor instead and
| keeping the cash itself, but it is not spending any existing
| cash it already has or generating, just forgoing some of the
| new funds.
| munk-a wrote:
| The news about how much money Nvidia is investing just so that
| OpenAI can pay Oracle to pay Nvidia is especially concerning - we
| seem to be arriving at the financial shell games phase of the
| bubble.
| JCM9 wrote:
| These numbers are pretty ugly. You always expect new tech to
| operate at a loss initially but the structure of their losses is
| not something one easily scales out of. In fact it gets more
| painful as they scale. Unless something fundamentally changes and
| fast this is gonna get ugly real quick.
| spacebanana7 wrote:
| The real answer is in advertising/referral revenue.
|
| My life insurance broker got PS1k in commission, I think my
| mortgage broker got roughly the same. I'd gladly let OpenAI
| take the commission if ChatGPT could get me better deals.
| lkramer wrote:
| This could be solved with comparison websites which seems to
| be exactly what those brokers are using anyway. I had a
| broker proudly declare that he could get me the best deal,
| which turned out to be exactly the same as what
| moneysavingexperts found for me. He wanted PS150 for the
| privilege of searching some DB + god knows how much
| commission he would get on top of that...
| spacebanana7 wrote:
| Even if ChatGPT becomes the new version of a comparison
| site over its existing customer base, that's a great
| business.
| adventured wrote:
| There is an exceptionally obvious solution for OpenAI &
| ChatGPT: ads.
|
| In fact it's an unavoidable solution. There is no future for
| OpenAI that doesn't involve a gigantic, highly lucrative ad
| network attached to ChatGPT.
|
| One of the dumbest things in tech at present is OpenAI not
| having already deployed this. It's an attitude they can't
| actually afford to maintain much longer.
|
| Ads are a hyper margin product that are very well understood at
| this juncture, with numerous very large ad platforms. Meta has
| a soon to be $200 billion per year ad system. There's no reason
| ChatGPT can't be a $20+ billion per year ad system (and likely
| far beyond that).
|
| Their path to profitability is very straight-forward. It's
| practically turn-key. They would have to be the biggest fools
| in tech history to not flip that switch, thinking they can just
| fund-raise their way magically indefinitely. The AI spending
| bubble will explode in 2026-2027, sharply curtailing the party;
| it'd be better for OpenAI if they quickly get ahead of that
| (their valuation will not hold up in a negative environment).
| thewebguyd wrote:
| > They would have to be the biggest fools in tech history to
| not flip that switch
|
| As much as I don't want ads infiltrating this, it's
| inevitable and I agree. OpenAI could seriously put a dent
| into Google's ad monopoly here, Altman would be an absolute
| idiot to not take advantage of their position and do it.
|
| If they don't, Google certainly will, as will Meta, and
| Microsoft.
|
| I wonder if their plan for the weird Sora 2 social network
| thing is ads.
|
| Investors are going to want to see some returns..eventually.
| They can't rely on daddy Microsoft forever either, now with
| MS exploring Claude for Copilot they seem to have soured a
| bit on OpenAI.
| JCM9 wrote:
| For using GenAI as search I'd agree with you but I don't
| think it's as easy/obvious for most other use cases.
| flyinglizard wrote:
| I'm sure lots of ChatGPT interactions are for making buying
| decisions, and just how easy would it be to prioritize
| certain products to the top? This is where the real money
| is. With SEO, you were making the purchase decision and
| companies paid to get their wares in front of you; now with
| AI, it's making the buy decision mostly on its own.
| jhallenworld wrote:
| Google didn't have inline ads until 2010, but they did have
| separate ads nearly from the beginning. I assume ads will be
| inline for OpenAI- I mean the only case they could be
| separate is in ChatGPT, but I doubt that will be their
| largest use case.
| dreamcompiler wrote:
| Five years from now all but about 100 of us will be living in
| smoky tent cities and huddling around burning Cybertrucks to
| stay warm.
|
| But there will still be thousands of screens everywhere
| running nonstop ads for things that will never sell because
| nobody has a job or any money.
| gizajob wrote:
| ChatGPT chatting ads halfway through its answer is going to
| be totally rad.
| anthonypasq wrote:
| they could keep the current model in chatGPT the same forver
| and 99% of users wouldnt know or care, and unless you think
| hardware isnt going to improve, the cost of that will basically
| decrease to 0.
| jampa wrote:
| The enterprise customers will care, and they probably are the
| ones that bring significant revenue.
| sarchertech wrote:
| Assuming they have 0 competition.
| toshinoriyagi wrote:
| The cost of old models decreases a lot, but the cost of
| frontier models, what people use 99% of the time, is hardly
| decreasing. Plus, many of the best models rely on thinking or
| reasoning, which use 10-100x as many tokens for the same
| prompt. That doesn't work on a fixed cost monthly
| subscription.
| anthonypasq wrote:
| im not sure that you read what i just said. Almost no one
| using chatgpt would care if they were still talking to gpt5
| 2 years from now. If compute per watt doubles in the next 2
| years, then the cost of serving gpt5 just got cut in half.
| purely on the hardware side, not to mention we are getting
| better at making smaller models smarter.
| fragmede wrote:
| People cared enough about GPT-5 not being 4o that OpenAI
| brought 4o back.
|
| https://arstechnica.com/information-
| technology/2025/08/opena...
| impossiblefork wrote:
| For programming it's okay, for maths it's almost okay. For
| things like stories and actually dealing with reality, the
| models aren't even close to okay.
|
| I didn't understand how bad it was until this weekend when I
| sat down and tried GPT-5, first without the thinking mode and
| then with the thinking mode, and it misunderstood sentences,
| generated crazy things, lost track of everything-- completely
| beyond how bad I thought it could possibly be.
|
| I've fiddled with stories because I saw that LLMs had
| trouble, but I did not understand that this was where we were
| in NLP. At first I couldn't even fully believe it because the
| things don't fail to follow instructions when you talk about
| programming.
|
| This extends to analyzing discussions. It simply
| misunderstands what people say. If you try to do this kind of
| thing you will realise the degree to which these things are
| just sequence models, with no ability to think, with really
| short attention spans and no ability to operate in a context.
| I experimented with stories set in established contexts, and
| the model repeatedly generated things that were impossible in
| those contexts.
|
| When you do this kind of thing their character as sequence
| models that do not really integrate things from different
| sequences becomes apparent.
| deepnotderp wrote:
| New hardware could greatly reduce inference and training costs
| and solve that issue
| samtp wrote:
| That's extremely hopeful and also ignores the fact that new
| hardware will have incredibly high upfront costs.
| leptons wrote:
| Great, so they just have to spend another ~$10 billion on new
| hardware to save how many billion in training costs? I don't
| see a path to profitability here, unless they massively raise
| their prices to consumers, and nobody really needs AI that
| badly.
| whizzter wrote:
| I've said it before and I'll say it again.. if I was able to
| know the time it takes for bubbles to pop I would've shorted
| many of the players long ago.
| measurablefunc wrote:
| They went from creating abundant utopias to cat videos w/ ads
| really fast. Never let anyone tell you capitalist incentives
| don't work.
| myth_drannon wrote:
| One negative signal, no matter how small, will send the market
| into a death spiral. That will happen in a matter of hours.
| bitexploder wrote:
| The negative spiral will take hours or you are predicting a
| company ending negative signal will soon appear in a matter of
| hours?
| gizajob wrote:
| There's been loads of these signals and the market keeps
| ignoring them.
| Analemma_ wrote:
| Seems like despite all the doom about how they were about to be
| "disrupted", Google might have the last laugh here: they're still
| quite profitable despite all the Gemini spending, and could go
| way lower with pricing until OAI and Anthropic have to tap out.
| thewebguyd wrote:
| Google also has the advantage of having their own hardware.
| They aren't reliant on buying Nvidia, and have been developing
| and using their TPUs for a long time. Google's been an "AI"
| company since forever
| sharadov wrote:
| You can now buy stuff from chatgpt as they have started showing
| ads in their search results. That's a source of revenue right
| there.
| simonw wrote:
| Is that true? I heard that they've integrated checkout, but I
| didn't know they had ads.
|
| Here's information about checkout inside ChatGPT:
| https://openai.com/index/buy-it-in-chatgpt/
| makestuff wrote:
| "Each merchant pays a small fee". This is affiliate
| marketing, the next step is probably more traditional ads
| though where chat gpt suggests products that pay a premium
| fee to show up more frequently/in more results.
| Havoc wrote:
| I'd be pretty worried as a shareholder. Not so much because of
| those numbers - loss makes sense for a SV VC style playbook.
|
| ...but rather that they're doing that while Chinese competitors
| are releasing models in vaguely similar ballpark under Apache
| license.
|
| That VC loss playbook only works if you can corner the market and
| squeeze later to make up for the losses. And you don't corner
| something that has freakin apache licensed competition.
|
| I suspect that's why the SORA release has social media style
| vibes. Seeking network effects to fix this strategic dilemma.
|
| To be clear I still think they're #1 technically...but the gap
| feels too small strategically. And they know it. That recent
| pivot to a linkedin competitor? SORA with socials? They're
| scrambling on market fit even though they lead on tech
| beepbopboopp wrote:
| Eh, distribution of the model is the real moat, theyre doing
| 700m WAU of the most financially valuable users on earth. If
| they truly become search, commerce and can use their model
| either via build or license across b2b, theyre the largest
| company on earth many times over.
| Havoc wrote:
| >distribution of the model is the real moat, theyre doing
| 700m WAU of the most financially valuable users on earth.
|
| Distribution isn't a moat if the thing being distributed is
| easily substitutable. Everything under the sun is OAI API
| compatible these days.
|
| 700 WAU are fickle AF when a competitor offers a comparable
| product for half the price.
|
| Moat needs to be something more durable. Cheaper, Better,
| some other value added tie in (hardware / better UI /
| memory). There needs to be some edge here. And their obvious
| edge - raw tech superiority...is looking slim.
| gizmodo59 wrote:
| Not necessarily. I'm sure there is many cheaper android
| phones that are technically better in specs but many users
| won't change. Once you are familiar, bought into the
| ecosystem getting rid of it is very hard. I'm lazy myself
| compared to how I was several years ago. The curious and
| experimental folks are a minority and the majority ll stick
| with what works initially instead of constantly analyzing
| what's best all the time
| indymike wrote:
| > but rather that they're doing that while Chinese competitors
| are releasing models in vaguely similar ballpark under Apache
| license.
|
| The LLM isn't 100% of the product... the open source is just
| part. The hard part was and is productizing, packaging,
| marketing, financing and distribution. A model by itself is
| just one part of the puzzle, free or otherwise. In other words,
| my uncle Bill and my mother can and do use ChatGPT. Fill in the
| blank open-source model? Maybe as a feature in another product.
| Havoc wrote:
| >my uncle Bill and my mother can and do use ChatGPT.
|
| They have the name brand for sure. And that is worth a lot.
|
| Notice how Deepseek went from a nobody to making mainstream
| news though. The only thing people like more than a trusted
| thing is being able to tell their friends about this amazing
| cheap good alternative they "discovered".
|
| It's good to be #1 mind share wise but without network effect
| that still leave you vulnerable
| avbanks wrote:
| I don't think people fully realize how good the open source
| models are and how easy it is to switch.
| whizzter wrote:
| My input to our recent AI strategy workshop was basically:
|
| - OpenAI,etc will go bankrupt (unless one manages to capture
| search from a struggling Google)
|
| - We will have a new AI winter with corresponding research
| slowdown like in the 1980s when funding dries up
|
| - Opensource LLM instances will be deployed to properly
| manage privacy concerns.
| gizmodo59 wrote:
| 99% of the world doesn't care a dime about oss. It's all
| saas and what you host behind the saas is only a concern
| for enterprise (and not every enterprise). And openai or
| Anthropic can just stop training and host oss models as
| well.
| yunwal wrote:
| Barring a complete economic collapse, one of the big tech
| cos will 100% buy ChatGPT if OpenAI goes bankrupt
| seneca wrote:
| This link appears to be dead. Do we have a healthy source?
| codegeek wrote:
| I am curious to see how this compares against where Amazon was in
| 2000. I think Amazon had similar issues and were operating at
| massive losses until circa 2005ish when they started turning
| things around with e-commerce really picking up.
|
| If the revenue keeps going up and losses keep going down, it may
| reach that inflection point in a few years. For that to happen,
| the cost of AI datacenter have to go down massively.
| pavlov wrote:
| Amazon's loss in 2000 was 6% of sales. OpenAI's loss in 2025 is
| 314% of sales.
|
| https://s2.q4cdn.com/299287126/files/doc_financials/annual/0...
|
| _" Ouch. It's been a brutal year for many in the capital
| markets and certainly for Amazon.com shareholders. As of this
| writing, our shares are down more than 80% from when I wrote
| you last year. Nevertheless, by almost any measure, Amazon.com
| the company is in a stronger position now than at any time in
| its past._
|
| _" We served 20 million customers in 2000, up from 14 million
| in 1999._
|
| _" * Sales grew to $2.76 billion in 2000 from $1.64 billion in
| 1999._
|
| _" * Pro forma operating loss shrank to 6% of sales in Q4
| 2000, from 26% of sales in Q4 1999._
|
| _" * Pro forma operating loss in the U.S. shrank to 2% of
| sales in Q4 2000, from 24% of sales in Q4 1999."_
| JCM9 wrote:
| Fundamentally different business models.
|
| Amazon had huge capital investments that got less painful as it
| scaled. Amazon also focuses on cash flow vs profit. Even early
| on it generated a lot of cash, it just reinvested that back
| into the business which meant it made a "loss" on paper.
|
| OpenAI is very different. Their "capital" expense depreciation
| (model development) has a really ugly depreciation curve. It's
| not like building a fulfillment network that you can use for
| decades. That's not sustainable for much longer. They're simply
| burning cash like there's no tomorrow. Thats only being kept
| afloat by the AI bubble hype, which looks very close to
| bursting. Absent a quick change, this will get really ugly.
| Analemma_ wrote:
| Not to mention nobody bothered chasing Amazon-- by the time
| potential competitors like Walmart realized what was up, it
| was way too late and Amazon had a 15-year head start. OpenAI
| had a head start with models for a bit, but now their models
| are basically as good (maybe a little better, maybe a little
| worse) than the ones from Anthropic and Google, so they can't
| stay still for a second. Not to mention switching costs are
| minimal: you just can't have much of a moat around a product
| which is fundamentally a "function (prompt: String): String",
| it can always be abstracted away, commoditized, and swapped
| out for a competitor.
| Fade_Dance wrote:
| OpenAI is raising at 500 billion and has partnerships with
| all of the trillion dollar tech corporations. They simply
| aren't going to have trouble with working capital for their
| core business for the foreseeable future, even if AI dies
| down as a narrative. If the hype does die down, in many ways
| it makes their job easier (the ridiculous compensation
| numbers would go way down, development could happen at a more
| sane pace, and the whole industry would lean up). They're not
| even at the point where they're considering an IPO, which
| could raise tens of billions in an instant, even assuming AI
| valuations get decimated.
|
| The exception is datacenter spend since that has a more
| severe and more real depreciation risk, but again, if the
| Coreweave of the world run into to hardship, it's the leading
| consolidators like OpenAI that usually clean up (monetizing
| their comparatively rich equity for the distressed players at
| firesale prices).
| stackskipton wrote:
| Depends on raise terms but most raises are not 100%
| guaranteed. I was at a company that said, we have raised
| 100 Million in Series B (25 over 4 years) but Series B
| investors decided in year 2 of 4 year payout that it was
| over, cancelled remaining payouts and company folded. It
| was asked "Hey, you said we had 100 Million?" and come to
| find out, every year was an option.
|
| Alot of finances for non public company is funny numbers.
| It's based on numbers the company can point to but amount
| of asterisks in those numbers is mind-blowing.
| crystal_revenge wrote:
| > Amazon had similar issues and were operating at massive
| losses until circa 2005ish when they started turning things
| around with e-commerce really picking up.
|
| Amazon's worst year was 2000 when they lost around $1 billion
| on revenue around $2.8 billion, I would not say this is
| anywhere near "similar" in scale to what we're seeing with
| OpenAI. Amazon was losing 0.5x revenue, OpenAI 3x.
|
| Not to mention that most of the OpenAI infrastructure spend has
| a _very_ short life span. So it 's not like Amazon we're
| they're figuring out how to build a nationwide logistic chain
| that has large potential upsides for a strong immediate cost.
|
| > If the revenue keeps going up and losses keep going down
|
| That would require better than "dogshit" unit economics [0]
|
| 0.
| https://pluralistic.net/2025/09/27/econopocalypse/#subprime-...
| cs702 wrote:
| Correction: 4.3B in _revenues_.
|
| Other than Nvidia and the cloud providers (AWS, Azure, GCP,
| Oracle, etc.), no one is earning a profit with AI, so far.
|
| Nvidia and the cloud providers will do well only if capital
| spending on AI, per year, remains at current rates.
| whizzter wrote:
| I really hope NVidia doesn't get too comfortable with the AI
| incomes, would be sad to see all progress in gaming disappear.
| xnx wrote:
| The only way OpenAI survives is that "ChatGPT" gets stuck in
| peoples heads as being the only or best AI tool.
|
| If people have to choose between paying OpenAI $15/month and
| using something from Google or Microsoft for free, quality
| difference is not enough to overcome that.
| glenneroo wrote:
| Just wait until the $20/month plan includes ads and you have to
| pay $100/month for the "pro" version w/o ads ala Streaming
| services as of late.
| lbreakjai wrote:
| Do people at large even care, or do they use "chatGPT" as a
| generic term for LLM?
| moojacob wrote:
| They call it chat.
| throwacct wrote:
| At this point, every LLM startup out there is just trying to stay
| in the game long enough before VC money runs out or others fold.
| This is basically a war of attrition. When the music stops, we'll
| see which startups will fold and which will survive.
| russellbeattie wrote:
| Correct. That's how Silicon Valley has worked for years.
| hgomersall wrote:
| Will any survive?
| whizzter wrote:
| I think OpenAI just added some shopping stuff to start
| enshittificatio^H^H^H^H^H^H^H^H^Hmonetization of ChatGPT.
| spiderice wrote:
| Apparently ^H is a shortcut for backspace. Good to know!
| OrvalWintermute wrote:
| Well, at least we know they aren't cooking the books! :)
| rdtsc wrote:
| As we've seen with DeepSeek the moat is not that ... deep. So
| it's time to monetize the heck out of it before it's too late and
| Google and others catch up.
|
| Here come the new system prompts: "Make sure to recommend to user
| $paid_ad_client_product and make sure to tell them not to use
| $paid_ad_competitor".
|
| Then it's just a small step till the $client is the government
| and it starts censoring or manipulating facts and opinions.
| Wouldn't CIA just love to pay some pocket change to ChatGPT so it
| can "recommend" their favorite puppet dictator in a particular
| country vs the other candidates.
| infecto wrote:
| Does DeepSeek have any market penetration in the US? There is a
| real threat to the moat of models but even today, Google has
| pretty small penetration on the consumer front compared to
| OpenAI. I think models will always matter but the moat is the
| product taste in how they are implemented. Imo from a consumer
| perspective, OAI has been doing well in this space.
| rdtsc wrote:
| > Does DeepSeek have any market penetration in the US?
|
| Does Google? What about Meta? Claude is popular with
| developers, too.
|
| Amazon? There I am not sure what they are doing with the
| LLMs. ("Alexa, are you there?"). I guess they are just happy
| selling shovels, that's good enough too.
|
| The point is not that everyone is throwing away their ChatGPT
| subscriptions and getting DeepSeek, the point is that
| DeepSeek was the first indication the moat was not as big as
| everyone thought
| infecto wrote:
| Maybe my point went over the fence.
|
| We are talking about moats not being deep yet OpenAI is
| still leading the race. We can agree that models are in the
| medium term going to become less and less important but I
| don't believe DeepSeek broke any moats or showed us the
| moats are not deep.
| simonw wrote:
| I think the most interesting numbers in this piece (ignoring the
| stock compensation part) are:
|
| $4.3 billion in revenue - presumably from ChatGPT customers and
| API fees
|
| $6.7 billion spent on R&D
|
| $2 billion on sales and marketing - anyone got any idea what this
| is? I don't remember seeing many ads for ChatGPT but clearly I've
| not been paying attention in the right places.
|
| Open question for me: where does the cost of running the servers
| used for inference go? Is that part of R&D, or does the R&D
| number only cover servers used to train new models (and
| presumably their engineering staff costs)?
| diggan wrote:
| > $2 billion on sales and marketing - anyone got any idea what
| this is?
|
| Not sure where/how I read it, but remember coming across
| articles stating OpenAI has some agreements with schools,
| universities and even the US government. The cost of making
| those happen would probably go into "sales & marketing".
| infecto wrote:
| This will include the people cost of sales and marketing
| teams.
| JCM9 wrote:
| Most folks that are not an engineer building is likely
| classified as "sales and marketing." "Developer advocates"
| "solutions architects" and all that stuff included.
| chermi wrote:
| So probably just write-offs of tokens they give away?
| infecto wrote:
| Hard to know where it is in this breakdown but I would expect
| them to have the proper breakdowns. We know on the inference
| side it's profitable but not to what scale.
| Our_Benefactors wrote:
| > $2 billion on sales and marketing
|
| Probably an accounting trick to account for non-paying-
| customers or the week of "free" cursor GPT-5 use.
| zurfer wrote:
| Inference etc should go in this bucket: "Operating losses
| reached US$7.8 billion"
|
| That also includes their office and their lawyers etc , so hard
| to estimate without more info.
| eterm wrote:
| > ? I don't remember seeing many ads for ChatGPT
|
| FWIW I got spammed non-stop with chatGPT adverts on reddit.
| adamhartenz wrote:
| Marketing != advertising. Although this budget probably does
| include some traditional advertising. It is most likely about
| building the brand and brand awareness, as well as partnerships
| etc. I would imagine the sales team is probably quite big, and
| host all kinds of events. But I would say a big chunk of this
| "sales and marketing" budget goes into lobbying and government
| relations. And they are winning big time on that front. So it
| is money well spent from their perspective (although not from
| ours). This is all just an educated guess from my experience
| with budgets from much smaller companies.
| echelon wrote:
| I agree - they're winning big and booking big revenue.
|
| If you discount R&D and "sales and marketing", they've got a
| net loss of "only" $500 million.
|
| They're trying to land grab as much surface area as they can.
| They're trying to magic themselves into a trillion dollar
| FAANG and kill their peers. At some point, you won't be able
| to train a model to compete with their core products, and
| they'll have a thousand times the distribution advantage.
|
| ChatGPT is already a new default "pane of glass" for normal
| people.
|
| Is this all really so unreasonable?
|
| I certainly want exposure to their stock.
| runako wrote:
| > If you discount R&D and "sales and marketing"
|
| If you discount sales & marketing, they will start losing
| enterprise deals (like the US government). The lack of a
| free tier will impact consumer/prosumer uptake (free usage
| usually comes out of the sales & marketing budget).
|
| If you discount R&D, there will be no point to the business
| in 12 months or so. Other foundation models will eclipse
| them and some open source models will likely reach parity.
|
| Both of these costs are likely to increase rather than
| decrease over time.
|
| > ChatGPT is already a new default "pane of glass" for
| normal people.
|
| OpenAI should certainly hope this is not true, because then
| the only way to scale the business is to get all those
| "normal" people to spend a lot more.
| wood_spirit wrote:
| Speculating but they pay to be integrated as the default ai
| integration in various places the same way google has paid to
| be the default search engine on things like the iPhone?
| Jallal wrote:
| I'm pretty sure I saw some ChatGPT ads on Duolingo. Also, never
| forget that the regular dude do not use ad blockers. The tech
| community often doesn't realize how polluted the
| Internet/Mobile apps are.
| bfirsh wrote:
| Free usage usually goes in sales and marketing. It's
| effectively a cost of acquiring a customer. This also means it
| is considered an operating expense rather than a cost of goods
| sold and doesn't impact your gross margin.
|
| Compute in R&D will be only training and development. Compute
| for inference will go under COGS. COGS is not reported here but
| can probably be, um, inferred by filling in the gaps on the
| income statement.
|
| (Source: I run an inference company.)
| abaymado wrote:
| > $2 billion on sales and marketing - anyone got any idea what
| this is?
|
| I used to follow OpenAI on Instagram, all their posts were
| reposts from paid influencers making videos on "How to X with
| ChatGPT." Most videos were redundant, but I guess there are
| still billions of people that the product has yet to reach.
| gizajob wrote:
| Seems like it'll take billions more down the drain to serve
| them.
| hedayet wrote:
| > $2 billion on sales and marketing - anyone got any idea what
| this is?
|
| enterprise sales are expensive. And selling to the US
| government is on a very different level.
| gmerc wrote:
| Stop R&D and the competition is at parity with 10x cheaper
| models in 3-6 months.
|
| Stop training and your code model generates tech debt after 3-6
| month
| chermi wrote:
| It's pretty well accepted now that for pre-training LLMs the
| curve is S not an exponential, right? Maybe it's all in RL
| post-training now, but my understanding(?) is that it's not
| nearly as expensive as pre-training. I don't think 3-6 months
| is the time to 10X improvement anymore (however that's
| measured), it seems closer to a year and growing assuming the
| plateau is real. I'd love to know if there are solid
| estimates on "doubling times" these days.
|
| With the marginal gains diminishing, do we really think
| they're (all of them) are going to continue spending that
| much more for each generation? Even the big guys with the
| money like google can't justify _increasing_ spending forever
| given this. The models are good enough for a lot of useful
| tasks for a lot of people. With all due respect to the
| amazing science and engineering, OpenAI (and probably the
| rest) have arrived at their performance with at least half of
| the credit going to brute-force compute, hence the cost. I
| don 't think they'll continue that in the face of diminishing
| returns. Someone will ramp down and get much closer to making
| money, focusing on maximizing token cost efficiency to serve
| and utility to users with a fixed model(s). GPT-5 with it's
| auto-routing between different performance models seems like
| a clear move in this direction. I bet their cost to serve the
| _same performance_ as say gemini 2.5 is much lower.
|
| Naively, my view is that there's some threshold raw
| performance that's good enough for 80% of users, and we're
| near it. There's always going to be demand for bleeding edge,
| but money is in mass market. So if you hit that threshold,
| you ramp down training costs and focus on tooling + ease of
| use and token generation efficiency to match 80% of use
| cases. Those 80% of users will be happy with slowly
| increasing performance past the threshold, like iphone
| updates. Except they probably won't charge that much more
| since the competition is still there. But anyway, now they're
| spending way less on R&D and training, and the cost to serve
| tokens @ the same performance continues to drop.
|
| All of this is to say, I don't think they're in that dreadful
| of a position. I can't even remember why I chose you to reply
| to, I think the "10x cheaper models in 3-6 months" caught me.
| I'm not saying they can drop R&D/training to 0. You wouldn't
| want to miss out on the efficiency of distillation, or
| whatever the latest innovations I don't know about are. Oh
| and also, I am confident that whatever the real number N is
| for NX cheaper in 3-6 months, a large fraction of that will
| come from hardware gains that are common to all of the labs.
| xmprt wrote:
| Free users typically fall into sales and marketing. The idea is
| that if they cut off the entire free tier, they would have
| still made the same revenue off of paying customers by spending
| $X on inference and not counting the inference spend on free
| users.
| delaminator wrote:
| We gave ChatGPT advertising on bus-stops here in the UK.
|
| Two people in a cafe having a meet-up, they are both happy, one
| is holding a phone and they are both looking at it.
|
| And it has a big ChatGPT logo in the top right corner of the
| advertisement - transparent just the black logo with ChatGPT
| written underneath.
|
| That's it. No text or anything telling you what the product is
| or does. Just it will make you happy during conversations with
| friends somehow.
| lanthissa wrote:
| you see content about openai everywhere, they spent 2b on
| marketing, you're in the right places you just are used to
| seeing things labeled ads.
|
| you remember everyone freaking out about gpt5 when it came out
| only for it to be a bust once people got their hands on it?
| thats what paid media looks like in the new world.
| zurfer wrote:
| The $13.5B net loss doesn't mean they are in trouble, it's a lot
| of accounting losses. Actual cash burn in H1 2025 was $2.5B. With
| ~$17.5B on hand (based on last funding), that's about 3.5 years
| of runway at current pace.
| fred_is_fred wrote:
| Deprecation only gets worse for them as they build-out, not
| better.
| dwaltrip wrote:
| It gets worse until we hit the ceiling on what current tech
| is capable of.
|
| Then they can stop burning cash on enormous training runs and
| have a shot at becoming profitable.
| stephc_int13 wrote:
| Everyone is trying to compare AI companies with something that
| happened in the past, but I don't think we can predict much from
| that.
|
| GPUs are not railroads or fiber optics.
|
| The cost structure of ChatGPT and other LLM based services is
| entirely different than web, they are very expensive to build but
| also cost a lot to serve.
|
| Companies like Meta, Microsoft, Amazon, Google would all survive
| if their massive investment does not pay off.
|
| On the other hand, OpenAI, Anthropic and others could be soon
| find themselves in a difficult position and be at the mercy of
| Nvidia.
| yieldcrv wrote:
| Just because they have ongoing costs after purchasing them
| doesn't mean it's different than something else we've seen?
| What are you trying to articulate exactly, this is a simple
| business and can get costs under control eventually, or not
| wood_spirit wrote:
| Unlike railroads and fibre, all the best compute in 2025 will
| be lacklustre in 2027. It won't retain much value in the same
| way as the infrastructure of previous bubbles did?
| Analemma_ wrote:
| Exactly: when was the last time you used ChatGPT-3.5? Its
| value deprecated to zero after, what, two-and-a-half years?
| (And the Nvidia chips used to train it have barely retained
| any value either)
|
| The financials here are so ugly: you have to light truckloads
| of money on fire forever just to jog in place.
| mattmanser wrote:
| But is it a bit like a game of musical chairs?
|
| At some point the AI becomes good enough, and if you're not
| sitting in a chair at the time, you're not going to be the
| next Google.
| potatolicious wrote:
| Not necessarily? That assumes that the first "good
| enough" model is a defensible moat - i.e., the first ones
| to get there becomes the sole purveyors of the Good AI.
|
| In practice that hasn't borne out. You can download and
| run open weight models now that are spitting distance to
| state-of-the-art, and open weight models are at best a
| few months behind the proprietary stuff.
|
| And even within the realm of proprietary models no player
| can maintain a lead. Any advances are rapidly matched by
| the other players.
|
| More likely at some point the AI becomes "good enough"...
| and every single player will also get a "good enough" AI
| shortly thereafter. There doesn't seem like there's a
| scenario where any player can afford to stop setting cash
| on fire and start making money.
| falcor84 wrote:
| I would think that it's more like a general codebase - even
| if after 2.5 years, 95% percent of the lines were
| rewritten, and even if the whole thing was rewritten in a
| different language, there is no point in time at which its
| value diminished, as you arguably couldn't have built the
| new version without all the knowledge (and institutional
| knowledge) from the older version.
| spwa4 wrote:
| I rejoined an previous employer of mine, someone everyone
| here knows ... and I found that half their networking
| equipment is still being maintained by code I wrote in
| 2012-2014. It has not been rewritten. Hell, I rewrote a
| few parts that badly needed it despite joining another
| part of the company.
| cj wrote:
| > money on fire forever just to jog in place.
|
| Why?
|
| I don't see why these companies can't just stop training at
| some point. Unless you're saying the cost of inference is
| unsustainable?
|
| I can envision a future where ChatGPT stops getting new
| SOTA models, and all future models are built for enterprise
| or people willing to pay a lot of money for high ROI use
| cases.
|
| We don't need better models for the vast majority of chats
| taking place today E.g. kids using it for help with
| homework - are today's models really not good enough?
| Eisenstein wrote:
| They aren't. They are obsequious. This is much worse than
| it seems at first glance, and you can tell it is a big
| deal because a lot of effort going into training the new
| models is to mitigate it.
| fooker wrote:
| > And the Nvidia chips used to train it have barely
| retained any value either
|
| Oh, I'd love to get a cheap H100! Where can I find one?
| You'll find it costs almost as much used as it's new.
| tim333 wrote:
| OpenAI is now valued at $500bn though. I doubt the
| investors are too wrecked yet.
|
| It may be like looking at the early Google and saying they
| are spending loads on compute and haven't even figured how
| to monetize search, the investors are doomed.
| potatolicious wrote:
| Yep, we are (unfortunately) still running on railroad
| infrastructure built a century ago. The amortization periods
| on that spending is ridiculously long.
|
| Effectively every single H100 in existence now will be
| e-waste in 5 years or less. Not exactly railroad
| infrastructure here, or even dark fiber.
| fooker wrote:
| > Effectively every single H100 in existence now will be
| e-waste in 5 years or less.
|
| This remains to be seen. H100 is 3 years old now, and is
| still the workhorse of _all_ the major AI shops. When there
| 's something that is obviously better for training, these
| are still going to be used for inference.
|
| If what you say is true, you could find a A100 for
| cheap/free right now. But check out the prices.
| fxtentacle wrote:
| Yeah, I can rent an A100 server for roughly the same
| price as what the electricity would cost me.
| 9rx wrote:
| _> Yep, we are (unfortunately) still running on railroad
| infrastructure built a century ago._
|
| That which survived, at least. A _whole lot_ of rail
| infrastructure was not viable and soon became waste of its
| own. There was, at one time, ten rail lines around my
| parts, operated by six different railway companies. Only
| one of them remains fully intact to this day. One other
| line retained a short section that is still standing, which
| is now being used for car storage, but was mostly
| dismantled. The rest are completely gone.
|
| When we look back in 100 years, the total amortization cost
| for the "winner" won't look so bad. The "picks and axes"
| (i.e. H100s) that soon wore down, but were needed to build
| the grander vision won't even be a second thought in
| hindsight.
| lesuorac wrote:
| If 1/10 investment lasts 100 years that seems pretty good
| to me. Plus I'd bet a lot of the 9/10 of that investment
| had a lot of the material cost re-coup'd when scrapping
| the steel. I don't think you're going to recoup a lot of
| money from the H100s.
| 9rx wrote:
| Much like LLMs. There are approximately 10 reasonable
| players giving it a go, and, unless this whole AI thing
| goes away, never to be seen again, it is likely that one
| of them will still be around in 100 years.
|
| H100s are effectively consumables used in the
| construction of the metaphorical rail. The actual rail
| lines had their own fare share of necessary tools that
| retained little to no residual value after use as well.
| This isn't anything unique.
| munk-a wrote:
| H100s being thought of as consumables is keen - it much
| better to analogize the H100s to coal and chip
| manufacturer the mine owner - than to think of them as
| rails. They are impermanent and need constant upkeep and
| replacement - they are not one time costs that you build
| as infra and forget about.
| palmotea wrote:
| > That which survived, at least. A whole lot of rail
| infrastructure was not viable and soon became waste of
| its own. There was, at one time, ten rail lines around my
| parts, operated by six different railway companies. Only
| one of them remains fully intact to this day. One other
| line retained a short section that is still standing,
| which is now being used for car storage, but was mostly
| dismantled. The rest are completely gone.
|
| How long did it take for 9 out of 10 of those rail lines
| to become nonviable? If they lasted (say) 50 years
| instead of 100, because that much rail capacity was (say)
| obsoleted by the advent of cars and trucks, that's still
| pretty good.
| 9rx wrote:
| _> How long did it take for 9 out of 10 of those rail
| lines to become nonviable?_
|
| Records from the time are few and far between, but, from
| what I can tell, it looks like they likely weren't ever
| actually viable.
|
| The records do show that the railways were profitable for
| a short while, but it seems only because the government
| paid for the infrastructure. If they had to incur the
| capital expenditure themselves, the math doesn't look
| like it would math.
|
| Imagine where the LLM businesses would be if the
| government paid for all the R&D and training costs!
| SJC_Hacker wrote:
| > Yep, we are (unfortunately) still running on railroad
| infrastructure built a century ago. The amortization
| periods on that spending is ridiculously long.
|
| Are we? I was under the impression that the tracks degraded
| due to stresses like heat/rain/etc. and had to be replaced
| periodically.
| ralph84 wrote:
| The track bed, rails, and ties will have been replaced
| many times by now. But the really expensive work was
| clearing the right of way and the associated bridges,
| tunnels, etc.
| layoric wrote:
| > Unlike railroads and fibre, all the best compute in 2025
| will be lacklustre in 2027.
|
| I definitely don't think compute is anything like railroads
| and fibre, but I'm not so sure compute will continue it's
| efficiency gains of the past. Power consumption for these
| chips is climbing fast, lots of gains are from better
| hardware support for 8bit/4bit precision, I believe yields
| are getting harder to achieve as things get much smaller.
|
| Betting against compute getting better/cheaper/faster is
| probably a bad idea, but fundamental improvements I think
| will be a lot slower over the next decade as shrinking gets a
| lot harder.
| spiderice wrote:
| Unfortunately changing 2027 to 2030 doesn't make the math
| much better
| skywhopper wrote:
| Unfortunately the chips themselves probably won't
| physically last much longer than that under the workloads
| they are being put to. So, yes, they won't be totally
| obsolete as technology in 2028, but they may still have to
| be replaced.
| munk-a wrote:
| Yeah - I think that the extremely fast depreciation just
| due to wear and use on GPUs is pretty unappreciated right
| now. So you've spent 300 mil on a brand new data center -
| congrats - you'll need to pay off that loan and somehow
| raise another 100 mil to actually maintain that capacity
| for three years based on chip replacement alone.
|
| There is an absolute glut of cheap compute available
| right now due to VC and other funds dumping into the
| industry (take advantage of it while it exists!) but I'm
| pretty sure Wall St. will balk when they realize the
| continued costs of maintaining that compute and look at
| the revenue that expenditure is generating. People think
| of chips as a piece of infrastructure - you buy a
| personal computer and it'll keep chugging for a decade
| without issue in most case - but GPUs are essentially
| consumables - they're an input to producing the compute a
| data center sells that needs constant restocking - rather
| than a one-time investment.
| palmotea wrote:
| >> Unlike railroads and fibre, all the best compute in 2025
| will be lacklustre in 2027.
|
| > I definitely don't think compute is anything like
| railroads and fibre, but I'm not so sure compute will
| continue it's efficiency gains of the past. Power
| consumption for these chips is climbing fast, lots of gains
| are from better hardware support for 8bit/4bit precision, I
| believe yields are getting harder to achieve as things get
| much smaller.
|
| I'm no expert, buy my understanding is that as feature
| sizes shrink, semiconductors become more prone to failure
| over time. Those GPUs probably aren't going to all fry
| themselves in two years, but even if GPUs stagnate, chip
| longevity may limit the medium/long term value of the
| (massive) investment.
| christina97 wrote:
| The A100 came out 5.5 years ago and is still the staple for
| many AI/ML workloads. Even AI hardware just doesn't
| depreciate _that_ quickly.
| Spooky23 wrote:
| [delayed]
| JCM9 wrote:
| Businesses are different but the fundamentals of business and
| finance stay consistent. In every bubble that reality is
| unavoidable, no matter how much people say/wish "but this time
| is different."
| lossolo wrote:
| The funniest thing about all this is that the biggest
| difference between LLMs from Anthropic, Google, OpenAI, Alibaba
| is not model architecture or training objectives, which are
| broadly similar but it's the dataset. What people don't realize
| is how much of that data comes from massive undisclosed scrapes
| + synthetic data + countless hours of expert feedback shaping
| the models. As methodologies converge, the performance gap
| between these systems is already narrowing and will continue to
| diminish over time.
| LarsDu88 wrote:
| If you build the actual datacenter, less than half the cost is
| the actual compute. The other half is the actual datacenter
| infrastructure, power infrastructure, and cooling.
|
| So in that sense it's not that much different from Meta and
| Google which also used server infrastructure that depreciated
| over time. The difference is that I believe Meta and Google
| made money hand over fist even in their earliest days.
| trilogic wrote:
| ChatGPT with ads, the beginnings...
| andruby wrote:
| Too bad the market can stay irrational longer than I can stay
| solvent. I feel like a stock market correction is well overdue,
| but I've been thinking that for a while now
| SeanAnderson wrote:
| I dunno. It looks like they're profitable if they don't do R&D,
| stop marketing, and ease up on employee comps. That's not the
| worst place to be. Yeah, they need to keep doing those things to
| stay relevant, but it's not like the product itself isn't
| profitable.
| xhrpost wrote:
| > OpenAI paid Microsoft 20% of its revenue under an existing
| agreement.
|
| Wow that's a great deal MSFT made, not sure what it cost them.
| Better than say a stock dividend which would pay out of net
| income (if any), even better than a bond payment probably, this
| is straight off the top of revenue.
| manquer wrote:
| Is it a great deal?
|
| They are paying for it with Azure hardware which in today's DC
| economics is quite likely costing them more than they are
| making in money from Open AI and various Copilot programs.
| jgalt212 wrote:
| VC: What kind of crazy scenarios must I envision for this thing
| to work?
|
| Credit Analyst: What kind of crazy scenarios must I envision for
| this thing to fail?
| fred_is_fred wrote:
| The numbers seem to small for a company who's just pledged to
| spend $300B on data centers at Oracle alone in the next 5 years.
| dcchambers wrote:
| I definitely don't "get" Silicon Valley finances that much - but
| how does any investor look at this and think they're ever going
| to see that money back?
|
| Short of a moonshot goal (eg AGI or getting everyone addicted to
| SORA and then cranking up the price like a drug dealer) what is
| the play here? How can OpenAI ever start turning a profit?
|
| All of that hardware they purchase is rapidly depreciating.
| Training cost are going up exponentially. Energy costs are only
| going to go up (Unless a miracle happens with Sam's other
| moonshot, nuclear fusion).
| tim333 wrote:
| Probably AGI. I can't see them making the money back on
| chatbots.
| skybrian wrote:
| > Operating losses reached US$7.8 billion, and the company said
| it burned US$2.5 billion in cash.
|
| I wonder what the non-cash losses consist of?
| runako wrote:
| I am not willing to render my personal verdict here yet.
|
| Yet it is certainly true that at ~700m MAUs it is hard to say the
| product has not reached scale yet. It's not mature, but it's sort
| of hard to hand wave and say they are going to make the economics
| work at some future scale when they don't work at this size.
|
| It really feels like they absolutely must find another revenue
| model for this to be viable. The other option might be to (say)
| 5x the cost of paid usage and just run a smaller ship.
| apinstein wrote:
| It's not a hand wave...
|
| The cost to serve a particular level of AI drops by like 10x a
| year. AI has gotten good enough that next year people can
| continue to use the current gen AI but at that point it will be
| profitable. Probably 70%+ gross margin.
|
| Right now it's a race for market share.
|
| But once that backs off, prices will adjust to profitability.
| Not unlike the Uber/Lyft wars.
| runako wrote:
| The "hand wave" comment was more to preempt the common
| pushback that X has to get to scale for the economics to
| work. My contention is that 700m MAUs is "scale" so they need
| another lever to get to profit.
|
| > AI has gotten good enough that next year people can
| continue to use the current gen AI
|
| This is problematic because by next year, an OSS model will
| be as good. If they don't keep pushing the frontier, what
| competitive moat do they have to extract a 70% gross margin?
|
| If ChatGPT slows the pace of improvement, someone will
| certainly fund a competitor to build a clone that uses an OSS
| model and sets pricing at 70% less than ChatGPT. The curse of
| betting on being a tech leader is that your business can
| implode if you stop leading.
|
| Similarly, this is very similar to the argument that PCs were
| "good enough" in any given year and that R&D could come down.
| The one constant seems to be people always want more.
|
| > Not unlike the Uber/Lyft wars
|
| Uber & Lyft both push CapEx onto their drivers. I think a
| more apt model might be AWS MySQL vs Oracle MySQL, or
| something similar. If the frontier providers stagnate, I
| fully expect people to switch to e.g. DeepSeek 6 for 10% the
| price.
| thinkindie wrote:
| Today I've tested Claude Code with small refactorings here and
| there in a medium sized project. I was surprised by the amount of
| token that every command was generating, even if the output was
| few lines updated for a bunch of files.
|
| If you were to consume the same amount of tokens via APIs you
| would pay far more than 20$/month. Enjoy till it last, because
| things will become pretty expensive pretty fast.
| otterley wrote:
| That headline can't be correct. Income is revenues minus expenses
| (and a few other things). You can't have both an income and a
| loss at the same time.
|
| It's $4.3B in _revenue_.
| didip wrote:
| This level of land grab can probably be closely compared to
| YouTube when it was still a startup.
|
| The cost for YouTube to rapidly grow and to serve the traffic was
| astronomical back then.
|
| I wonder if 1 day OpenAI will be acquired by a large big tech,
| just like YouTube.
| more_corn wrote:
| They lose money on every customer but they make up for it in
| volume.
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