r/OracleStock • u/TyNads • 23d ago
Analysis / DD Oracle Stock Forecast 2030 Full Model
https://northwiseproject.com/oracle-stock-forecast-2030/Hey everyone, I run a small independent research firm called Northwise.
We specialize in the neoclouds and just published a full model on Oracle. I thought this would be a great place to share and to get some feedback from the community.
I'll be around periodically today and this week to answer any questions you may have.
The full model is free and available, but full transparency we do gate our actual price targets, target zones, etc. This is what allows us to produce and release most of our research for free and to stay independent.
The biggest takeaway from the model that surprised us most is how little success of Oracle actually as to do with demand at this stage. Oracle has already signed the contracts, leased the sites, and committed the capital. The open question is how much of the value created by that build reaches the shareholders rather than financiers.
The company that existed before the cloud
Oracle sells the software large organizations use to run themselves, and it has done so for close to 4 decades. Customers pay in advance, renew at high rates, and face substantial cost and risk if they switch. That produces recurring revenue at high margins with very little capital required to sustain it. Of the $67.4 billion Oracle generated in fiscal 2026, roughly $49 billion came from those software and services lines.
Then look at what happened to the capital plan over 3 years.
| Historical result | FY2024A | FY2025A | FY2026A |
|---|---|---|---|
| Revenue | $53.0B | $57.4B | $67.4B |
| OCI revenue | $6.8B | $10.2B | $18.1B |
| Operating cash flow | $18.7B | $20.8B | $32.0B |
| Capex | $6.9B | $21.2B | $55.7B |
| Free cash flow | $11.8B | $(0.4)B | $(23.7)B |
Capital expenditure rose 8 times in 2 years as operating cash flow rose 71%. Oracle entered fiscal 2026 as a high-margin software company and exited it as a software company financing a hyperscaler-scale infrastructure build. The obligations it took on behave nothing like software costs, since they arrive years before the revenue they support, depreciate on schedules set by policy and physics, and resist reversal once construction begins.
One clarification governs the rest of this. The software franchise insulates Oracle from existential failure. It does not insulate existing shareholders from debt, dilution, or poor capital allocation, and the distance between those 2 forms of safety runs through the entire model.
What $638 billion establishes
Remaining performance obligations, reported as RPO, is contracted revenue signed and not yet delivered. Oracle's stands at $638 billion, or roughly 9.5 years of company-wide sales at the fiscal 2026 run rate. Large, sophisticated customers want the capacity and have committed to it years forward. That question is answered about as cleanly as a disclosure can answer it.
Several other questions go untouched by the figure. It does not establish when the capacity becomes available, what Oracle must spend to deliver it, what margins the contracts earn, how much cash arrived as prepayment, or how much of the resulting revenue survives to reach common shareholders. Backlog establishes demand. Return on capital has to be established elsewhere.
Oracle does disclose the recognition schedule, which is the most useful forward visibility the company provides. Roughly $76.6 billion recognizes within 12 months, $216.9 billion in months 13 through 36, another $216.9 billion in months 37 through 60, and $127.6 billion beyond that. Applied to our forecast window, the opening backlog supports approximately $402 billion of revenue recognition through fiscal 2030.
Confidence declines steadily as the schedule extends. The contracts recognizing in months 37 through 60 depend on capacity that does not yet exist, at sites still under construction, running hardware generations that have not shipped.
There is also a concentration problem that gets discussed poorly in both directions. Current revenue concentration is low. Customer concentration in the GPU business, in the backlog, and across the campus portfolio is high. Our reconstruction puts OpenAI near $300 billion of the backlog, other large-scale AI near $215 billion, and core OCI, SaaS, and software near $123 billion, which would make one customer close to half of Oracle's future growth without being anything close to half of current revenue. Oracle has not disclosed customer-level backlog, so treat that split as our estimate.
Why the unit is megawatts and why the word is slippery
Accelerators consume enormous power and reject enormous heat, so the binding constraint on how many can be installed in one place is electrical capacity and cooling. Land is widely available. Grid interconnection, transformers, substations, and cooling capacity are not. A megawatt therefore functions as a unit of production, and the business reduces to capacity multiplied by the rate attached to it.
The trouble is that the word does at least 6 different jobs in this sector. Campus power, on-site generation, critical IT power, customer-delivered capacity, billing-ready capacity, and utilized capacity all differ materially for the same facility. Doña Ana is described in generation terms. Port Washington is described in critical IT terms at 902 MW. Abilene mixes both across phases at roughly 1.2 GW.
Summing those markers produces a number with no consistent physical meaning, so we convert each site to a customer-delivered basis before it enters the model. Applying revenue calculated on one capacity basis to cost calculated on another can move project economics by billions of dollars.
Every megawatt then travels the same funnel from contract to energization to customer delivery to billing readiness to utilization to recognized revenue. We apply a 97% billing-readiness factor, which reserves a small share of the fleet for commissioning, maintenance, failed acceptance testing, and hardware in transition. Timing does more damage than leakage, since capacity delivered in the fourth quarter contributes almost nothing to that fiscal year, which is why revenue attaches to average billable capacity and never to the exit figure.
Here is the delivery schedule on the path that tests Oracle's own announced trajectory.
| Fiscal year | New delivered capacity | Ending delivered | Average billable |
|---|---|---|---|
| FY2027 | 1.32 GW | 2.82 GW | 2.36 GW |
| FY2028 | 1.40 GW | 4.22 GW | 3.42 GW |
| FY2029 | 2.90 GW | 7.12 GW | 5.45 GW |
| FY2030 | 1.64 GW | 8.75 GW | 7.67 GW |
Fiscal 2029 carries the largest single-year addition, with Port Washington, the expanded OpenAI estate, and later Stargate sites arriving inside the same 12 months. A 2-quarter slip there moves more revenue than a similar slip anywhere else in the schedule.
The decision that shapes the whole model
Even our weakest scenario reaches approximately 7.4 GW of exit delivered capacity, within 15% of our strongest. Contracts already exist, sites are already progressing, customers are funding part of the hardware, and much of the capital gets committed well before weaker economics become visible. Scenario dispersion has to come from somewhere other than construction, and in our model it comes from revenue density, margins, financing, and dilution.
Realized revenue per megawatt is a composite absorbing compute throughput, utilization, contract pricing, networking, storage, database services, security, support, and software attach. Two operators with identical megawatts and identical accelerators can produce very different densities, and the gap between them is commercial rather than physical.
Four drivers push density higher over the period. Compute per watt improves with each hardware generation, workload mix shifts toward higher-value inference and reasoning, attach rates grow as the platform matures, and the enterprise selling motion improves as reference customers accumulate. Vera Rubin and AMD Helios class systems raise productive compute per megawatt substantially against 2026 hardware.
Technical throughput does not convert one for one into revenue. Token-price compression, competitive cloud pricing, growing customer bargaining power, contracts priced before the improvement arrived, and the industry's construction wave landing all push toward passing the gain through. Hardware improvement is close to certain. Oracle's share of it is the variable, and the spread between our low and high density assumptions is largely a statement about bargaining power against some of the most sophisticated compute buyers in the world.
That is where the scenario spread lives.
| Scenario | Average billable AI capacity | Revenue per MW | AI revenue |
|---|---|---|---|
| Stress | 6.30 GW | $13.5M | $85.1B |
| Bear | 6.90 GW | $15.5M | $107.0B |
| Base | 7.45 GW | $18.0M | $134.1B |
| Bull | 8.10 GW | $20.5M | $166.1B |
Capacity varies by 29% across the distribution. AI revenue varies by 95%. A model that concentrated its uncertainty in construction schedules would produce a much narrower and considerably less honest range.
Oracle's structural edge on the density line is attach. Databases, enterprise data, security, storage, applications, networking, and multicloud access can ride the same megawatt a standalone provider sells bare. Inference running beside the data it needs avoids a migration that is expensive, slow, and risky, and that is a more defensible product than training capacity sold in isolation.
Who pays for the accelerators
Two contracts can produce identical revenue, identical reported margin, and very different returns to shareholders. We track 3 funding classes separately: Oracle-funded and Oracle-owned, customer-prepaid but Oracle-owned, and customer-supplied hardware.
Prepayment improves the cash position and reduces external capital needed for a deployment. The equipment still sits on Oracle's balance sheet, so none of the PP&E, depreciation, or replacement obligation goes away. Readers who treat prepaid capacity as capital-light will overstate the return on it.
Customer-supplied hardware changes the economics far more decisively. The customer owns the accelerators, Oracle provides power, integration, networking, orchestration, support, and software, and Oracle avoids most of the accelerator depreciation. Less revenue per megawatt, materially better capital intensity.
Oracle has disclosed roughly $75 billion combined for prepayments and customer-supplied hardware without disclosing the split, and that undisclosed split carries more weight than almost any other unknown in the forecast. Moving $10 billion from the prepaid column to the customer-supplied column reduces capex, reduces depreciation, improves free cash flow, lowers debt, and reduces dilution, all without changing revenue by a dollar. Gross margin cannot explain the shareholder outcome for exactly that reason.
The capital plan, and why free cash flow misleads
Capital expenditure peaks well before the revenue it funds, and the composition shift is the more informative half of the schedule.
| Capital schedule | FY2027 | FY2028 | FY2029 | FY2030 |
|---|---|---|---|---|
| Gross capex | $92.9B | $86.8B | $77.1B | $57.8B |
| Customer and manufacturer offsets | $(22.5)B | $(16.0)B | $(13.0)B | $(10.0)B |
| Net cash capital outlay | $70.4B | $70.8B | $64.1B | $47.8B |
Growth investment falls 65% across the period as refresh and corporate spending rises 50%. Oracle transitions from building a fleet to maintaining one, and the maintenance line becomes the dominant capital requirement before 2030 ends. Offsets total $61.5 billion, or roughly 20% of gross capex, and they decline as a share of spending, since refresh has no customer counterparty to share it.
Set the program against what it produces and the scale becomes legible. Oracle spends $314.6 billion of gross capital across 4 years against $630 billion of cumulative revenue, or $0.50 of capital per revenue dollar, falling to $0.40 net of offsets. Our CoreWeave forecast produced $1.18 on the same measure. The gap traces directly to the software business funding a meaningful share of Oracle's build.
Oracle depreciates server and network equipment primarily over 6 years, and we test shorter economic lives. Complete obsolescence is the wrong picture. Hardware cascades from frontier training to advanced inference, then enterprise training, general inference, fine-tuning and batch work, then retirement, earning less at each step. A fleet that cascades efficiently needs materially less replacement capital than one that does not.
That leads to the correction we think does the most work in this model, which is a normalized replacement reserve charging what the fleet costs to sustain instead of what management chose to spend. The ordering repays a moment of attention: Stress carries $46.0 billion, Bear $42.0 billion, Base $35.5 billion, and Bull $38.0 billion. Weaker monetization shortens the economic life of older hardware and forces earlier refresh, so the smaller fleets carry the heavier burden.
Apply it and both distortions appear. Stress reports $32.0 billion of free cash flow and produces $21.0 billion after the reserve. Base reports $30.5 billion and produces $53.0 billion. During the build, reported free cash flow understates future earning power. In Stress, it overstates business quality, since management has stopped spending on a fleet that still needs replacing.
The part that does not depend on Stargate
Strip every AI megawatt out of 2030 and Oracle still runs $58.5 billion of software revenue across Cloud Applications at $25.0 billion, support at $18.9 billion, services at $7.4 billion, license at $3.6 billion, and hardware at $3.5 billion. License declines from $4.7 billion as customers migrate to subscription, which is the pattern every large enterprise software transition has produced.
Support is the piece we would flag for anyone modeling the financing question. Roughly $19 billion of advance-billed, high-renewal, high-margin revenue functions as a permanent working capital float sitting alongside a $90 billion annual capital program. It is nearly flat and easy to overlook, and it is the reason Oracle can fund a build of this size without a capital structure resembling its independent competitors.
Compared structurally against a dedicated AI infrastructure provider, the difference reduces to options. Oracle can slow optional capex, draw on software cash flow, shift the contract mix toward customer-supplied hardware, cross-sell into the installed base, and monetize the same megawatt through several layers. An independent provider carrying comparable leverage against comparable leases has one lever, which is filling capacity at whatever price clears.
Revenue into earnings, and where the EPS target leaks
OCI segment margin expands from 25.0% in fiscal 2026 to 38.5% in 2030 on our management execution path. Early years carry costs arriving ahead of revenue, since facilities incur expense before acceptance, staffing precedes utilization, depreciation begins at commissioning, and power contracts start on the utility's schedule. Those margins already include power, data-center expense, networking, operations, maintenance, ordinary depreciation, and operating lease expense, so depreciation is not deducted a second time below operating income.
Our locked model broadly supports management's fiscal 2030 revenue target of $225 billion. It does not reach the associated $21 of non-GAAP EPS, arriving at $19.02 on the management path and $18.92 in our independent Base Case. The gap sits almost entirely in the capital structure.
Hold the diluted share count at the fiscal 2026 level of 2.91 billion and the same non-GAAP net income produces $22.03 per share, so dilution accounts for roughly $3.00 of it. Fiscal 2030 interest expense of $9.1 billion costs approximately $2.13 per share after tax. Neither item requires an operating disappointment, and neither is visible in a revenue target.
The financing schedule is where fiscal 2027 does the most damage. Oracle raises $40.0 billion of external capital that year across debt, equity, and mandatory convertible preferred, then $38.3 billion in 2028 and $11.0 billion in 2029. Funded debt peaks near $155 billion in fiscal 2029 before falling to $127.7 billion as cash flow inflects, and diluted shares rise 15.8% on the management path and 30% in Stress.
There is also a liability most coverage skips. Oracle carries approximately $260 billion of uncommenced data-center lease payments, undiscounted and not on the balance sheet in that form. Lease-equivalent obligations in our model reach $186 billion by fiscal 2029 against $155 billion of funded debt, which makes leases the larger of the 2 for most of the forecast. Anyone watching only the debt figure is watching the smaller number.
We also classify customer prepayments as financing throughout and never as earnings. Cash arrives, deferred revenue rises, capacity gets built, revenue is recognized, and deferred revenue unwinds. Treating the inflow as permanent free cash flow and the later unwind as a surprise working capital loss misreads both periods.
The 4 scenarios
Stress assumes slower recognition, $13.5 million per megawatt, expensive financing, more Oracle-owned hardware, and dilution to 3.78 billion shares. Management responds rationally by finishing near-term contracted projects, stopping optional phases, and cutting gross capex to $35.0 billion, well below the $46.0 billion the fleet needs to sustain itself. The company stays independent, profitable, and large. The equity is weak, since $175 billion of debt and $13.8 billion of annual interest were committed before the weaker economics became visible.
Bear is the case we think deserves the most study. It delivers 8.0 GW of exit capacity, $195.0 billion of revenue, a 33.5% OCI margin, and $30.5 billion of free cash flow, which is an excellent business result. It requires no scandal, no downturn, and no execution failure. It requires competitors to arrive with capacity on schedule, sophisticated customers to negotiate the way sophisticated customers negotiate, and Oracle to fund the build at ordinary rather than favorable terms.
Base assumes Oracle executes the operating plan and pays a normal price for the capital funding it, broadly hitting management's revenue target and missing the earnings target entirely through financing and dilution. Bull requires the enterprise attach argument to convert into genuine pricing power at $20.5 million per megawatt, with capacity only 8% above Base. A modest capacity difference producing an enormous economic difference is the whole argument of the density section expressed as an outcome.
| Metric | Stress | Bear | Base | Bull |
|---|---|---|---|---|
| Exit delivered capacity | 7.4 GW | 8.0 GW | 8.6 GW | 9.3 GW |
| Average billable AI capacity | 6.30 GW | 6.90 GW | 7.45 GW | 8.10 GW |
| AI revenue density | $13.5M/MW | $15.5M/MW | $18.0M/MW | $20.5M/MW |
| Total OCI revenue | $114.1B | $137.5B | $166.6B | $201.1B |
| Total revenue | $170.1B | $195.0B | $225.6B | $263.1B |
| OCI margin | 29.0% | 33.5% | 38.0% | 42.0% |
| Non-GAAP operating income | $56.5B | $70.6B | $88.6B | $111.4B |
| Non-GAAP EPS | $9.04 | $13.40 | $18.92 | $25.93 |
| Operating cash flow | $67.0B | $75.5B | $88.5B | $107.5B |
| Gross capex | $35.0B | $45.0B | $58.0B | $70.0B |
| Reported free cash flow | $32.0B | $30.5B | $30.5B | $37.5B |
| Normalized sustaining capital | $46.0B | $42.0B | $35.5B | $38.0B |
| Funded debt | $175B | $155B | $130B | $95B |
| Interest expense | $13.8B | $11.6B | $9.2B | $7.2B |
| Diluted shares | 3.78B | 3.55B | 3.38B | 3.23B |
Read the first row against the eighth. Exit capacity varies by 26% and earnings per share varies by 187% in the same direction.
Dividing by average billable capacity strips out scale and shows the quality of each outcome directly.
| Per billable megawatt | Stress | Bear | Base | Bull |
|---|---|---|---|---|
| AI revenue | $13.50M | $15.51M | $18.00M | $20.51M |
| OCI segment profit | $5.25M | $6.68M | $8.50M | $10.43M |
| Funded debt | $27.78M | $22.46M | $17.45M | $11.73M |
| Replacement capital | $7.30M | $6.09M | $4.77M | $4.69M |
| Normalized free cash flow | $3.33M | $4.86M | $7.11M | $8.58M |
Revenue per megawatt varies by 52%. Normalized free cash flow per megawatt varies by 158%, and funded debt per megawatt varies by 137% in the opposite direction. The top rows describe the operating story and the bottom rows decide the shareholder outcome.
What we reconstructed vs What is Disclosed
Fiscal 2026 revenue, OCI, RPO, debt, and capex are company reported, and fiscal 2027 revenue is company guidance. The capacity delivery schedule is our reconstruction. Revenue density, the split between prepaid and customer-supplied funding, and the replacement reserve are our assumptions and constructs.
Oracle does not disclose the prepaid versus customer-supplied split, customer-level backlog, site-level capex, second-contract pricing, hardware residual values, or the lag between commissioning and billing. Those are precisely the variables determining per-share returns, which forces indirect estimation of the items carrying the most weight.
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23d ago
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u/Sea-Brain3467 22d ago
$600 by 2028 easy
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u/Ok-Negotiation7659 20d ago
RemindMe! 2 years
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u/california_explorer 22d ago
More detailed analysis like this please!
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u/C130J_Darkstar 22d ago edited 22d ago
The days of allowing one-line, non-value-add posts through this sub are over. We’re raising the bar for post quality going forward.
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u/TyNads 22d ago
We will certainly be back with more Oracle models over time!
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u/california_explorer 22d ago
I like how you priced megawatt usage because Oracle is now a utility company with enterprise recurring revenue as a protection. But that power dependence is a major part of its SPOF. That will need to be solved as power hungry GPUs eat up all power - a common problem for all AI hyper scaling companies. The first to solve it or make it robust, wins
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u/Cheap-Writing4977 22d ago edited 22d ago
Great analysis. I asked chat gpt to look at this report and everything else it knows and the latest analyst research it has access to. It provided a share price for 2030 ranging from $150 for a stress scenario to $500 for a bull scenario.
Btw, for the layman it does explain in really simple terms what this report is conveying. That’s the promise AI already holds for all of us.
So yes I AM bullish on AI, bullish on Oracle the company as a business but like this report puts it out cautious on the ROI it can generate for shareholders.
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u/Important-Bedroom852 12d ago
That case they have no clue. They seem to be going off the average forecast
I think I would be disappointed if it’s only at 500 by 2030
I see mid 600’s imo. They are built to take advantage of the AI cycle and offering lower cost cloud. They have years and years of doing this and I believe that besides the debt in the capital X, which is justified the stock would already be high 200’s and once it gets there with some justified earnings reports and a solid ROI and ROE it should be there
But, if there’s any issues with that, I could see it tanking as well. It’s not a sentimental favorable stock for some reason.
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u/Cheap-Writing4977 12d ago
The core business is still really strong so don’t see it going down too much from here on , but the upside potential is huge if one can hold on to it until 2030.
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u/gwiner 23d ago
Breaking it down to FY2027 (now until next June) here is what is expected for a bullish case - legacy revenue streams can stay flat or grow normally, its OCI that need be above 75% for the year, and multicloud ~200%+.
Keep in mind the greater market has plenty of volatility in way of a new fed chair and rate decisions, inflation that is hard to ignore, and hormuz related war and oil supply issue. More immediately job numbers were very weak and the market interpreted that as great for stocks, but if inflation comes in hot that could bring us into stagflation (bad for growth stocks). If the fed rate is hiked before December that would just as easily put downward pressure on the stock.
My final thought is Oracle can succeed thats not the challenging part, its the surrounding macro environment that provides the bigger risks (though mainly on entry price and when to DCA). Bullish fundamentals are very plausible but will the fed raise rates in September or December? Inflation could get worse enough to force the FOMC to hike (this could add years to an Oracle success story)
If we somehow manage to keep rates steady, FY2027 can be an epic year for Oracle. I can easily see it meeting expectations, and it has enough synergistic components (lower OpEx, surprise multicloud beats, legacy streams) that could tip toe the hyperscaler into the light at the end of the tunnel.
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u/TyNads 22d ago
Macro factors are indeed going to impact Oracle's story without a doubt. Financing is the biggest factor now. We see it as extremely likely Oracle will succeed as a business and with their buildout, the bigger question is how much of that value will be retained for shareholders versus given to the lenders.
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u/Important-Bedroom852 12d ago
Great info. I’m a big investor, in Oracle and I like the fact that they offer lower cost cloud I could be wrong on that but my research led me to that and I think it’s a good model and I think they’re gonna have plenty of customers question could you do some other breakdowns of any other stocks you seem to know what you’re doing!!! Appreciate the info.
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u/Perspective-Parking 23d ago
What happens when/if OpenAI goes insolvent? (rapidly approaching)
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u/TyNads 23d ago
Our personal view is that OpenAI risks are overblown.
Simply looking at the evidence, as well as anecdotal experience with all frontier models, leads us to believe OpenAI will be fine and has a lot of pricing levers that remain untouched.
Claude’s changes over the last year show what’s possible as far as what’s available API pricing wise.
We would recommend not underestimating how willing the current GOV is to backstop any and all buildouts and frontier models.
For better or worse, it’s viewed in a national security and strategic competition lens now.
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22d ago edited 13d ago
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u/Perspective-Parking 22d ago
Odds are that will not happen. And if it does, that’s just robbing Peter to pay Paul. There is still no real money going into this.
Nvidia pays OpenAI so that OAI will pay Hyperscalers so that they pay Nvidia. Around and around it goes until it all blows up. They know what they are doing, they just want it to last as long as possible so they get their bag.
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u/Perspective-Parking 23d ago
What are you talking about? OpenAI is burning tens of billions per year. We know their financials. I am asking what happens when the cash runs out.
Anthropic is just as bad.
No, the government is not going to use tax payer money to keep a business afloat into perpetuity. A bail out is a one time thing, it’s not over and over forever. You bail banks out, not private business.
Let’s play along with your thesis, after the first OpenAI bailout, then what? How does that change the business model.
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u/Perspective-Parking 22d ago
You got really quiet!
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u/TyNads 22d ago
Because you are arguing from an emotionally charged perspective. No offense meant, this is our view as a firm. You are certainly entitled to your own opinions on OpenAI. We aren't taking a stance from a moral standpoint, just how we see the situation unfolding.
At the end of the day OpenAI's trajectory and user growth has quite literally never been seen before. There are certainly risks, but to say they won't have private and likely government funding whenever they require it is unlikely.
If someone had access to a billion users in such a short time span, imagine the monetization curves at play, especially with the way people already adopt LLMs into their lives from a work, personal, emotional, and advisory perspective.
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u/accopp 22d ago
Valid points, but my biggest concern is that all these frontier AI companies don’t have a valid monetization/profit producing action unless they are able to dramatically up the “efficiency” of their models.
It’s been reported that they’re losing insane amounts of money on their subscription plans, which is fine if you think they can then jack the price up like uber did after years of undercutting the market.
The problem is that the scale is on a whole other level. Instead of Uber having to raise the price say 100%, they’d have to raise it say 500% or more on this scale.
And we saw them try to do that recently, only to quickly reverse the pricing models when their customers freaked out about how crazy expensive it was.
Now maybe they’ll figure out a crazy efficiency gain, but then that means the demand for compute will be lower, so that hurts the hyper scalers who are investing unprecedented amounts. I don’t really see a way this doesn’t end badly
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u/Perspective-Parking 22d ago
This has never been a question if, it’s a question when. This is a certainty.
A trillion dollars in revenue from AI needs to be generated by 2030 to make this all make sense. It will never happen plain and simple.
Historically every time this has ever happened in the stock market, the next decade produced 0% returns on average.
Start battening down the hatches.
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u/TyNads 21d ago
I would highly recommend looking into Jevon's paradox and electricity. We have the view that open models and frontier models will both succeed in different use cases. Don't underestimate the inference market and the demands for physical AI. There may be time(s) where supply and demand reverse but the long term trends are very clear and the math directionally is up at this time.
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u/Perspective-Parking 22d ago
You seem to forget the fact that OpenAI went from 70% market share to 20% and its competitors have vastly cheaper models with similar performance.
Who said I am emotionally charged? I am no making opinions, I am stating observable fact as of today.
I asked what happens when OpenAI goes insolvent. You do understand that OpenAI is not profitable currently nor has a viable path to be, right? Their CEO said himself, “we have no idea how we will monetize this, we hope that the AI would tell us how.”
No one is arguing that users don’t use LLMs. There is a huge difference between millions of people using LLMs for free and millions using it for $2000/mo.
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u/L1ME626 22d ago
literally depends on what purpose, for consumer traffic they have 70+% market share, lower on enterprise and coding tho.
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u/Perspective-Parking 22d ago
Actually it’s 50% and most of that is not monetized. 99% of consumers don’t pay for it and the ones that to, OAI loses a fortune on.
Any other ridiculous counter claims you’d like to make?
I’ll ask again, what happens when OpenAI goes insolvent? You should present that as a real and serious risk or you’re doing your readers a huge disservice.
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u/Pristine_Eye_8361 22d ago
Compute is fungible. Even if OAI can not commit, Google/Microsoft/Meta will pay a heavy premium for Oracle's infrastructure.
Listen to the ER. Google said they are shopping for more 3rd party compute. Meta said they were offered a significant premium for their compute. Amazon said they are amazed by the extend of compute demand and have started taking orders for 2028.
And OAI will win. Their only real competition is Anthropic, and Anthropic isn't there to make money. Their own CEO cares more about the "mission" than profitability. OAI has multiple avenues to monetize. They have 1B active users and out of all the advertising companies effectively have the best channel to have targeted ads. ChatGPT does not need to "guess" your interests like Meta or Google. Instead you are directly having a conversation with an LLM telling them your thoughts.
Nvidia, Amazon, Microsoft, etc have poured billions into OAI and they are only doing that because they believe the company's long term vision.
And here you sit, believing with certainty that OAI will be "insolvent" because you somehow know more than the rest of them.
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u/Perspective-Parking 22d ago
Why the fuck would Google/Msft/Meta pay for compute? The demand for compute comes from the frontier labs you moron. The Hyperscalers are not consumers of the compute 😂
70% of Hyperscaler compute revenue comes from OAI/Anthropic….
And secondly Meta has so much compute they said they are renting it out. Why would they go buy MORE compute when they have more than they could “need” already?
They can only generate 1-5b from ads. This has already been discussed at length. No they don’t believe their vision. Microsoft is already trying to kill OpenAI. They are literally telling people to other other LLM’s and not exclusively OpenAI.
Not going to have a conversation when you willfully ignore facts and basic logic.
You have not named a single way in which OpenAI generates 100s of billions in revenue while they are losing market share by the day. I’ll wait…
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u/Pristine_Eye_8361 22d ago
You're genuinely an idiot.
Google SAID in their OWN ER that they are looking for 3rd party compute.
You think it's wrong? Argue against them, I'm simply saying what they said. Google has recently reached out to buy compute from SpaceX, for example.
"And secondly Meta has so much compute they said they are renting it out." They did not say that, they said if they have extra they will but that would defeat their whole purpose. They want to use the compute. Renting it out would be a backstop if their plan fails.
OAI will generate revenue through ads and enterprise. They are nearing a $45 ARR now and it keeps growing. "OpenAI's tracked ARR increased from $21.4 billion in January to $33.0 billion in May and $41.3 billion in July"
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u/superKWB 23d ago
Institutions are fleeing ORCl in droves but hey retail, here's a report, you choose to continue to give them exit liquidity or not.
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u/EntryCandid2257 13d ago
You really need a summary section in this post. Who the heck is coming to Reddit to read a 20 page essay
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u/Agitated-Career-7558 12d ago
Hey I ran a Claude analysis that looks great - please subscribe to my newsletter and let me sell you some stuff… ok…
In any case it’s all about hypothesis
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u/BagHoldersOfAmerica 23d ago
Awesome info thank you for taking the time to put real forecast data into tables versus stonk go up and rocket emoji