API

FuriaDePantera

Margins on inference are very high on API. Subscripiton overall are probably not too subsidized if at all. Take into account not every user max it out. Many probably even pay and not use it. Subscription is a minimal part of their revenue stream but it is the entry point to capture more demand (as the free tier is).

DigitalArbitrage

They are either massively overcharging their API prices or they are massively subsidizing their subscriptions. If you assume the API pricing is actual pricing and apply it to subscriptions it looks like they are subsidizing customers.

HanzJWermhat

I don’t believe fundimentals continue to improve. If anything the opposite. I work for a large bank and we’re working on AI integration. We’re hiring 8 engineers just to try and implement it. Implement something we have little evidence will work as advertised. That money is being spent at cost by the bank not to the AI vendor. If anything part of the reason is to reduce vendor cost. We use open models for inference. And are trying to maximize our quality of output per token spend. Meanwhile there is in many ways a pricing war. The new benchmark is benchmark/token cost. Anthropic is starting to lose customers because of this. There is 0 moat for the frontier labs when you can switch providers near instantly with an API call. Coupled with a firm realization in my company that it’s clear LLM tech is good for things like coding and analytics but it blows chunks at other work. That’s not a harness problem it’s a knowledge problem. Strategy, internal comms, context none of that is available to train on and even if they did it’s not enough to meaningfully produce a good model. That’s why LLMs are still pretty bad at coding natively iOS apps there’s orders of magnitude less swift code than there is Java and python code. Same for strategy. Made more complex by the fact you can’t test strategy you can’t test comms, you can’t test roadmaps against a test suite. All Unverifiable work. So I think the fundamentals look bad actually even if you stopped training today inference demand just for coding and the tasks LLMs are ok at wouldn’t be enough to justify the fixed costs of the data centers. Everything is highly subsidized by debt

kasthack-refresh

Yup, complete waste of money. Recently, I started using AI to vibe code what are basically compiler plugins([.NET Compiler platform SDK API](https://learn.microsoft.com/en-us/dotnet/csharp/roslyn-sdk/) it you're interested) that apply refactorings to the entire codebase. AI-generated parts of PRs are now typically under 500 lines and they can be reviewed for bugs, while massive changes applied to the source are deterministic and simply rely on the correctness of the plugins instead of having AI to burn through the endless amounts of tokens to fix the same issue across thousands of files and hallucinate along the way.

dinyee

I recently connected to the Moomoo OpenD API using Python to run some automated trading strategies. It's still in testing.

s48L55

Not just that, but the REA thing is a new problem. Everyone understands the "if consumers are gone, what happens to companies selling products" angle. But what happens to *every* software company when you can just point an LLM (conceivably any LLM - hosted/API via Anthropic, local inference using an open weight Chinese model, etc) at a piece of software and tell it to make a copy. More investors in the AI space need to read the book "Fully Automated Luxury Communism" - because Bastani makes an argument saying information, and by extension information labor, is infinitely replicable and impossible to contain. If that's true (and it's increasingly becoming evident that it is), any economy dependent on information labor has no fundamental value. An infinite pile of gold is definitionally worthless.

CranberryIcy1788

Ok, that's good info! I downloaded E-trade's sample dev API Java app that I want to expand to look at some of these patterns and alert me since my job doesn't really afford me the ability to constantly watch.

3iverson

$29 at API rates is so little…

Kryslor

My company has every developer on an enterprise max plan and it let's you use a lot of tokens for a fraction of the cost if you were paying per token. Unless you need to use a bunch of agents simultaneously or need the API for some automated stuff then you shouldn't be paying per token because it's a lot less economically viable.

mojomarc

SaaS may be sticky but it's AaaS (it isn't that, either. It's just AI and traditional software for the client). The majority of what they do is just serving up an API that front ends an inference capability. That's not at all sticky. This is why all of the AI companies are pouring so much into RnD--if the new model is able to run faster, or cheaper, or has better inference, it is trivial to replace it. Look at Microsoft Copilot: you can literally hit a pull down and change the model from Claude to OoenAI to a multitude of other models. So assuming that Anthropic has sticky revenue is wishful thinking. They're trying to sign customers to long term contracts for the clients, but that only lasts one contract cycle if they can't maintain a lead.

Zestyclose-Durian-97

Everyone and their mother is using free google AI and free tiers of Claude and ChatGPT. Then you have the people who use the 20 euros subscribtions. Then you have the businesses who straight up quit using it once they had to deal with API pricing. Then maybe you have like 2% of the usage that is actually profitable. That's an industry worth billions, no trillions on a multi-trillion buildout.

NanNullUnknown

Is it per API price? $29 might be one or two messages then,

Winter_Current9734

We have the tool to just hook it up to a sandbox with graph API. Big Pharma here.

zer00eyz

\>  its getting to a point where every 1$ spent on tokens gets you more than 1$ worth of economic output, Outside the circle of AI doing things around AI show me where this is happening? I will give you two softballs because they are the only two: 1 - Grindr is having success. But they were an already a strong engineering organization with a culture of experimentation. 2. Kraken Technologies - is using some AI but is mostly just a software spin off. There have been a lot of "attributions" to AI (Ikea, BofA) and a lot of "one time gains" that don't turn into "shows up every quarter in the margins". \> I don't know how you are so confident that demand stops outstripping supply ... I don't disagree that we may shift to more local, self hosted infrastructure in the future, there is just literally no way to get more power right now. I pointed you to a 100k system for 2 devs that plugs into a regular wall outlet and has a top of the line NVIDIA server chip in it. Or 40k of Mac studios that use less power. The shift is happening NOW and not at data center scale. The fact that I can even buy that NVIDIA chip says "data center market is saturated". Those systems are CapEx, they get accounted for over their lifetime of ownership: read 24-48 months. Congratulations CTO you just took 4k a month of variable spend and turned it into a nice 1000 a month per dev over the next 4 years. The accountants are happy and the bottom line looks better for a one time impact to your free cash flow. >**Business & Enterprise Scale:** Anthropic reports serving **over 300,000 business customers**, which includes enterprise API channels. Over 114,000 companies explicitly use Claude, and **75% of Anthropic's total revenue** comes directly from API and model usage.  Dont think this is going to be the way? Well meta is one of the first to start cutting back: [https://finance.yahoo.com/technology/article/meta-has-an-ai-advantage-openai-and-anthropic-cant-replicate-100000733.html](https://finance.yahoo.com/technology/article/meta-has-an-ai-advantage-openai-and-anthropic-cant-replicate-100000733.html) And every CTO with a dev blowing 4k a month is the first one looking for an off ramp. The people who are going to do this first, are the most valuable customers. \> there is just literally no way to get more power right now.  If this is REALLY a hard wall then the cost of Ram and Compute are going to drop like a stone. 10k MacBooks start running bleeding edge models - The expensive cloud compute is left to be "customer service bots" and they start looking way over priced to everyone involved. No matter how you slice it there is massive demand and a clear path to massive price pressure \> the whole point is that over time the same level of capability/intelligence/output, gets cheaper, 50 billion of payments a year on compute. Anthropic doesn't cover that right now. It needs its customers to spend 2x what they are today without using more than its allotted infrastructure. Based on its current margins it can cut prices roughly in half. Any more than that and it needs to find efficiency or spend more to earn more. None of that is realistic - they are going to go for an uber style rug pull - see "local agents"

Available_Thanks_887

i think Thursday last week the market snipped out the the stagnation grows in the AI Frontier Labs when OpenAI number release(Sam might did it on purpose to ruin Anthropic IPO or forced them to give real number) , and the chart has been damaged and today Anthropic’s Q3 revenue ($16.8bn) confirms the signals a structural shift from exponential growth to a commercial plateau for frontier model LABs. This is the fears that enterprise seat expansion and API volume are failing to keep pace with hyper inflated of like potential $7 trillion by 2030 capital deployments according to Gartner. The tech is good but not for 7.4 trillion build out that is way too expensive. Institutions are waiting at the exit doors and pumping the market !!!! be safe out there

FightOnForUsc

My employer just changed a couple months ago (we were using cursor and had requests not paying API rates). But now you just need VP approval. I have about $600 I can allocate to cursor, Claude, or OpenAI. And while it’s not great at everything, it is amazing how much it can do for me at times

itsalwayscalls

I do not. Their S1 will lift the market when people extrapolate out high margin API revenue over lesser fixed training costs.

Minute-Animator-376

In my personal opinion Microsoft is quietly winning. They don't care for 1st 2nd and 3rd spot with their models. They actually provide quite good solutions to business that are accessible to anyone with proper training that is not that hard and provide trainings and certifications too for a business. The progress on AI models will be slowing down or looking on Open AI lack of compute nowadays it already started. Free Chinese open source models are catching up - if they are deemed as secure by Microsoft and offered to a business they will destroy Anthropic and Open AI market where next best thing is no longer needed. Some s&p 500 companies are already restricting access to better but more costly models. It is also hard to calculate ROI on AI "assistance" but if throughput rises due to nearly free AI models that are good enough this is no brainer vs paying API costs - soon I guess 10k$ from Anthropic or Open AI to replace one random dude from India.

zer00eyz

TSMC's who built the chips is 2x normal margins. Nvidia who sold the chips is 2x normal margins. The ram systems is 2-3x the normal margin. Core weave bought them with debt and 60 percent margins. Anthropic runs them at 70 percent margins. There is absolutely massive demand for ai - can Anthropic get to 85 billion in revenue to cover the 50 billion a year in commitments (take or pay) it has? Yes. Can anthropic sustain that? The 200 dollar a month subsidized API plan gets you about $1000 (api price) worth of tokens a week. It isn't quite enough to keep a full time developer busy but close, and it makes the math easy. An NVIDIA system that will push enough tokens to support 3-4 developers is $120K MSRP ($99k preorder). Realistically 2 devs can keep this machine busy all day, and as a bonus running over night. Does 100k of OPEX to Anthropic compete with 100K of CapEx that you can depreciate? The instant demand stops outstripping supply (and it will) that same system goes down to 60k and then 40k... At 60k most CTO's would buy 2, at 40 they would buy 3, because there are people in an org who can make use of large numbers of agents running concurrently. Concurrent agents that Andrej Karpathy is talking about in a [tweet](https://thenewstack.io/karpathy-levie-ai-capability-gap/) (Sorry cant link to X) just aren't worth it if your paying API prices but if you own your compute it starts to make more sense. NVIDIA does NOT have a lock on this market either - 40k (per developer) Of M5 Apple Studio (512MB) is already a target for quite a few organizations that want to curtail that 1000 dollar a week spend - and is going to put pressure on the previously listed NVIDIA system. Every org that is going to make heavy use of AI (the customers anthropic wants) is also going to realize that the day time needs of the users who use it less turns into a bigger pool of agents running concurrently outside business hours. Meanwhile someone else is going to build a core weave equivalent at half the price, putting pressure on anthropic's margins and commitments. All the big players (Meta, Alphabet, Amazon) have their own chips, made at TSMC, that cut out NVIDA (but still buy premium ram). All of them have their own "intelligence" offering that is going to be competing with Anthropic/OAI - And some of them (MS, Meta) are actively curtailing their use of anthropic - in favor of their own internal tools. They might not be as good, but that difference is so marginal when you are running a large number of them concurrently.

Logical-Clerk-1571

It seems Truth API is working lmao

2020isgreat

yeah I'm going to rent GPUs from a hyperscaler instead of using the deepseek API which is somehow chapear

owowthatreallysucked

Do you know how API pricing works? I'm not assuming anything, I know that the margins of dollars spent per token is ridiculous, it's just that it's not seen as net profits yet because the capex build out and training of new models is eating it all up

Creative_Strike8202

Yeah but you will pay Anthropic's API at the rate they choose and it will automatically asign you the cheapest agent that can perform the task optimally.

shared_ptr

They’re mostly not: majority of the revenue comes from API pricing which is very profitable for Anthropic. All their costs come from training which is always about protecting their lead so they can achieve the next year of growth which pays for it. I don’t know where this levels of, it may have started already. But if they stopped training now or dialled it down then Opus 5.5 is a killer model and can justify a lot of spend from enterprise.

No_Entertainment5968

Si l'API d'IBKR est exclue, trouver un courtier qui offre à la fois une large disponibilité internationale et une API REST/WebSocket solide et adaptée aux développeurs pour l'intégration d'options peut s'avérer délicat. Vous pourriez jeter un œil à IG : ils disposent d'une présence internationale très étendue dans de nombreux pays où Schwab n'est pas accessible, et leur API est plutôt bien documentée pour les intégrations tierces. Une autre option axée sur les développeurs à envisager est Alpaca, bien que l'ouverture de comptes à l'international dépende des pays concernés. Enfin, AvaTrade (en particulier via leur plateforme AvaOptions) vaut également le détour. Ils bénéficient d'une solide régulation multi-juridictionnelle et couvrent de nombreux marchés internationaux. Cependant, gardez à l'esprit qu'une grande partie de leur infrastructure d'API repose sur MetaTrader (MT4/MT5) ; il faudra donc vérifier si leurs points d'accès API pour les options correspondent aux besoins d'intégration d'Optionsmith.

farsightfallen

It's really hard to build a business that costs 100s billions to train a model, and then other companies can just distill it down for 10s mns, that's 90% effective, for 99% of the work by volume. Unless they get some IP protection or regulatory capture, it's going to be an uphill climb. Claude is amazing, but if I had to pay API prices, there are better solutions for most of the work. Maybe strategic use of fable or w/e for release review.

Maxdiegeileauster

Who cares about subscription. Every large company pays API pricing, the subs are just to get people hooked.

CBFball

Enterprises are all API based and on a per token basis?

Bitter_Election_7518

You missed my first part. B2B is their profit center. Analysts have their API margins at like 70-80%+. And that $4k in credits is at API list price, not what it actually costs anthropic to serve it, so most $200 subs are pretty much break-even or better for them. Only the heavy users are getting subsidized. It's okay to eat a little on power users to gain market share when enterprise is paying the bills. The fact that anthropic already posted an adjusted operating profit this soon is pretty impressive considering they're arguably the top lab for model innovation and spending a ton on R&D.

HustlinInTheHall

This is not comparing their costs though, it is comparing API costs. 

Mondanivalo

of course not. I did my due diligence and my API call rates are low enough that I fly under the radar of rate limitation. Plus I have CRON jobs that pull and store data for the entire SNP500 and Russel2000 every day for EU and US. I have day open/high/low/close bars for some stocks going back 40 years. So if i want to see historical data, that comes from my own database, i dont need to hammer the API for it anymore. https://preview.redd.it/syfo83v43jvh1.png?width=758&format=png&auto=webp&s=f9d35dee5ed3b383342c47c7094c268f667be395

owowthatreallysucked

Token API prices is set by the company, the actual active cost is the electricity really and when I run local ai llm models I undervolt my GPU and performance is still the same I bet they do that aswell

Ryzensai

Bc the tech isn’t for you. Or any of us. We are data cows being milked right now. The good compute goes to corps/teams pulling from the API.

buzzberg_ai

For US company financials, I use the SEC’s EDGAR APIs as a starting point. The data is free, but you still have to reconstruct what was available at each point in time. Two checks matter: 1. Clean the numbers before handing them to the LLM. Map and calculate in Python using explicit rules, then check the output against the filings. Watch units, quarterly versus year-to-date cash flows, and which share count you’re using. The SEC’s aggregated XBRL APIs cover standard, company-wide facts; custom-tagged items can require the original filing. SEC API documentation. 2. Use the date the information became available to your strategy. A December 31 period end isn’t a December 31 publication date. For example, 13F reports are generally due within 45 days after quarter-end. Keep each value tied to its original filing and version, so later revisions don’t leak into earlier decisions. SEC’s 13F guidance. For intraday tests, SEC acceptance time is only a proxy for availability. Allow for publication, processing and execution delays. SEC timestamp guidance. Fixing the dates addresses one source of look-ahead bias. A drop in simulated returns doesn’t prove the rest of the backtest is sound.

CartographerAble9446

this will never happen because claude subscription doesnt allow you to actually integrate claude to your own tools. Most of those wrapper startups need API, and API prices are expensive, you won't spawn 100 agents for 100 different workers, that is actually more expensive than hiring workers

gavinderulo124K

But thats compared to API prices which they have crazy margins on. So in reality the 200 dollar usage costs them closer to 1k.

Kaastu

Every tech company building AI tools in-house is already model agnostic. Eventually we will create internal benchmarking tools and always choose the cost-performance optimized model for each task and tool. Even now I can choose whichever API I want for our in-house AI Platform. We will absolutely not continue paying the premiums of the first movers after the field has cought up.

TopBite7720

I was referring to the API profit margins which anyone with a brain the size of a pea would deduce given the context. Anyway, assuming a 90% margin on their API product, their subscription would be around break-even. CapEx isn’t something that just magically evaporates. It’s accounted for via D&A. You’re just parroting the same talking points of Michael Burry.

TopBite7720

I was referring to the API profit margins which anyone with a brain the size of a pea would deduce given the context. Anyway, assuming a 90% margin on their API product, their subscription would be around break-even. CapEx isn’t something that just magically evaporates. It’s accounted for via D&A. Either way, you’re just parroting the same talking points of Michael Burry.

Reply_Stunning

just ask any frontier model this simple question: \`\`in 2026 so far, is Anthropic in net profit, with honest calculations ?\`\` While Anthropic’s business is scaling at an unprecedented rate and generating massive cash inflows from enterprise API usage, an honest calculation that factors in equity compensation, cloud partner cuts, and debt revaluations means **they remain deeply net-unprofitable**as they prepare for their IPO. \[[1](https://www.tradingkey.com/analysis/stocks/us-stocks/262215419-anthropic-discloses-q3-financials-first-time-ipo-what-investors-need-knowtradingkey), [2](https://www.morningstar.com.au/stocks/anthropics-leaked-financials-reflect-fast-growth-not-2-trillion-valuation)\] 1. "Adjusted" Operating Profit vs. Net Profit 2. Gross vs. Net Revenue Booking

Jaded_Impress_5160

And it's already cheaper to pay bulk API rates with non-US hosted Anthropic models, once they've leased out their models for use by resellers (AWS Bedrock and the like) they have no control over what a customer then sees. Ads are not the way.

Witty-Collection932

It is complicated because the product SLA matters. S3 is after all an API, and you need a dozen IAMs to get through to use it. Despite that, S3 is the most successful cloud object store ever. Why? Because it works at unprecedented scale up/down any time, 99% uptime. And AWS has DCs in 50 countries in the world to make that fast and cost efficient. That is what matters. The point is OpenAI, Anthropic, Google have sales team in every major country to make it seamless for many countries to use. They apply for legal rights and all. Once you switch to third party models from China, good luck navigating the complex security language and complying with every law yourself. I find the talk of using lesser intelligent models for everyday work bizarre. This is like interviewing 5 candidates and deciding that you will hire the 3rd intelligent guy since that is sufficient for your work. Says nobody ever. You give out the best offer and hope the best guy joins. Same for models, you hope the cost of the most intelligent model comes down. If you are working with a less intelligent model than your competitor, it will bite you ultimately. FOMO.

Stonp

There’s no way any person would seriously use my product if my API was sending their data to China

m-c91624

The API can be interchangeable while deployment isn’t: teams still need to rerun evals on their own edge cases and clear security review before switching. That’s some friction.

Original-Poet1825

Wonder if compute or API credits are going to end up being publicly tradable like oil at some point…

cinnapear

It all comes down to cost. Today, local AI (GLM 5.3 Flash, for example) is good enough for most AI purposes. It can run on ~$12,000 worth of hardware and 4 users can use it at once. Any fiddliness involved in getting local models like it to run is going to disappear when prebuilt appliances start appearing. No one cares about OS because these things are interacted with through web browsers and coding harnesses and API endpoints. As a bonus, data stays inhouse (attractive for HIPAA). If companies like OpenAI and Anthropic are vastly subsidizing costs for users, at some point that is going to have to change... meanwhile local hardware is going to get cheaper. I think we're looking at a situation like America Online... right now the gates to a new world are controlled by a few big players, but soon everyone will have their own path.

callesucia

I don't know, I'm not in a position where I know those things, I just know what the CEO says during our quarterly meetings. I do know API usage is very expensive and you're giving out free (and sometimes proprietary) data to OpenAI or Anthropic, while having an in-house solution the data is your own, the advances you make on the model are your own and the product is your own and the technical know-how is your own.

SliceAndDime

the issue with Anthropic and OpenAI API cost with corporate is that most non tech people will litteraly set tokens on fire to count the number of words in a word document (Seen multiple times)

CaffeinatedT

>Yes, that’s why I said operating profit. Training cost is CapEx, and CapEx is not included in operating profit. These are common accounting rules. Accountancy doesn’t work like a wordplay game. If you file your biggest ongoing operating cost under “Capex” then people will ask questions like “Does this mean the model training will eventually stop?". Likewise excluding partner rev-share deductions is also pretty non-credible considering that’s about 6-8 billion in revenue depending who you ask so that’s about 5-10% of 2026 revenue already. The point of accountancy is to account for things not to play stupid philosophical word games as many financial criminals find out when they go too far down this road. The legal system/Capital doesn’t give a fuck about getting cute with special snowflake definitions of profit. >Do you claim to know what Anthropic’s operating profit is? If you do, you know more than the public does. Some commentators say it’s up to 90% margin. In that case they are already making profits. Let’s leave aside that you don’t understand enough to realise those margins are on their API products which are the full priced ones aimed at enterprises that no-one wants to use... As said before If I exclude my mortage and bills and just count my salary then I am insanely profitable on a Month to month basis too. If they were genuinely profitable they’d be slapping that shit everywhere and not pulling these Enron-ass shenanigans so It’s pretty easy to take with a grain of salt.

Serious_Shape_5518

The main issue with AI is switching cost. You have basically zéro switching cost besides changing an API key

callesucia

I work in a big tech company. A couple of years ago thet got us all access to Claude and ChatGPT and really pushed for everyone to use it. Two or three months later they announced they were working on an in house model based on open source ones. Nine months ago they removed access to Claude and ChatGPT to the non coding areas (HR, Sales, Marketing, etc) and forced them to use the in house model. At first the in house model sucked bad, but I tested it a while ago and it worked as good as Claude in some instances. I have friends in other departments and they seem to be happy with how much it has progressed. According to the CEO, it's cheaper to pay for the infrastructure to run an in house model than the API costs for Claude and ChatGPT, with the bonus that the company is in complete control of the input data. The goal is to stop using external models in the next 3 years. I believe many big companies will do the same in the next few years. You don't need frontier models to do much of what companies are doing. Anthropic and OpenAI will eventually be bought by bigger companies with other streams of revenue, like Amazon or Google, because their model isn't really profitable.

BlindPilot9

Tell me you don’t understand tech monopolies without telling me you don’t understand tech monopolies. You’re sitting here looking at a 2025 balance sheet like a boomer accountant analyzing an 1890s railroad. **This is the classic dealer playbook.** Uber burned billions for a decade subsidizing cheap rides until yellow cabs vanished. Amazon ran near zero profit for twenty years to build AWS and logistics. Right now, AI labs are practically giving compute away to hook every engineer, Fortune 500 company, and startup on their ecosystem. Once companies embed Claude so deep into their workflow that ripping it out would collapse operations, Anthropic jacks up the API pricing. Classic customer lock-in. I didn't wait for the bell to ring and bought ticker **D X Y Z** to get exposure to Anthropic and Revolut before retail even knows what ticker to type. Here’s the actual bull thesis: 1. **Claude is currently king.** Ask literally any dev—Sonnet and Opus run circles around the competition where it actually matters. 2. **It isn't going away.** It’s only getting faster at automating your job. 3. **The enterprise spend freight train.** AI budgets aren’t shrinking; enterprise and consumer spend will compound year-over-year for the next 5+ years. 4. **The national security moat.** Do you honestly think the Pentagon, DARPA, and US intelligence agencies are going to run government infrastructure on Chinese open-weight models? Zero chance. Domestic frontier labs have an impenetrable moat. 5. **Generational public debut.** How often do you get the chance to buy a foundational monopoly shaping the next three decades of human industry at IPO? Name one that flopped completely. **The Play:** Snag shares at IPO if you get the allocation. When the inevitable lockup expiration chop hits the 6-month trading range, back up the truck and average down like a true degenerate. Bears R f\~<ked. 🚀🚀🚀 Sincerely yours, Fable 5.1

BlindPilot9

Tell me you don’t understand tech monopolies without telling me you don’t understand tech monopolies. You’re sitting here looking at a 2025 balance sheet like a boomer accountant analyzing an 1890s railroad. **This is the classic dealer playbook.** Uber burned billions for a decade subsidizing cheap rides until yellow cabs vanished. Amazon ran near zero profit for twenty years to build AWS and logistics. Right now, AI labs are practically giving compute away to hook every engineer, Fortune 500 company, and startup on their ecosystem. Once companies embed Claude so deep into their workflow that ripping it out would collapse operations, Anthropic jacks up the API pricing. Classic customer lock-in. Can’t wait for the bell to ring? Just buy **$DXYZ** right now. It gives you direct private-market exposure to Anthropic and Revolut before retail even knows what ticker to type. Here’s the actual bull thesis: 1. **Claude is currently king.** Ask literally any dev—Sonnet and Opus run circles around the competition where it actually matters. 2. **It isn't going away.** It’s only getting faster at automating your job. 3. **The enterprise spend freight train.** AI budgets aren’t shrinking; enterprise and consumer spend will compound year-over-year for the next 5+ years. 4. **The national security moat.** Do you honestly think the Pentagon, DARPA, and US intelligence agencies are going to run government infrastructure on Chinese open-weight models? Zero chance. Domestic frontier labs have an impenetrable moat. 5. **Generational public debut.** How often do you get the chance to buy a foundational monopoly shaping the next three decades of human industry at IPO? Name one that flopped completely. **The Play:** Snag shares at IPO if you get the allocation. When the inevitable lockup expiration chop hits the 6-month trading range, back up the truck and average down like a true degenerate. Bears r f--ked. 🚀🚀🚀

BananasAndBrains

If you pay subscription prices you just use the best model for everything. But when a company has to pay API prices 80% of tasks can be done by GLM 5.3 or Kimi K3. Anthropic can have the best frontier model and still lose 80% of AI use cases.

SouJuggy

I don't think people will stay with them if they're forced to pay up monthly. Especially not "power users". It's as simple as pointing your agent to a competitor's API and boom, you're done. Nothing locally changes. I hear DeepSeek 4.1 Flash is roughly 90% as good as Claude 5.5, but it's way cheaper. There's also western companies looking to build frontier level opensource models, so in the future you won't even need to rely on Chinese models. I think Anthropic will make good money short term, but I don't see them lasting long-term. Google looks much better imo.

ImplementBrief44

if the "Full" comes only via a subscription right now, that’s a clear signal Meta doesn’t yet trust people—especially devs—to have direct API access for a model that claims to beat GPT‑6 in benchmarks. the high consumption rates are a red flag for any subscription that’s a handful of gigs a month. pretty sure the pricing isn’t lining up with what the average r/StockMarket person gets from the free model, and the data privacy concerns don’t help its perception of worth.

AVRVM

They tried this earlier this year. They had such massive pressure to lower prices they had to revert some of their API pricing changes.

Away_Candidate_4746

Counterpoint - Stackoverflow was once one of the highest volume websites on the internet and they are now almost entirely dead from LLMs. Reddit is valuable as a content farm for AIs to train on, however now that most of the content is AI generated on Reddit, the value as a source of human input into the models is diminishing which is where much of their API-based revenue comes from. Godspeed 🫡

TheBestIsaac

Except we have the books for these companies. It doesn't say specifically what the per million token cost is to the company but we can see that they are losing money and where. We know how much they spend in different areas and things. Hang on. Maybe I can ask GPT to sort this out.. It said that costs could range from 2.5% to 25% of the API charge. It changes heavily on how efficient they are with GPU allocations and some other stuff.

cjami

For the rest of us that build AI products, forming the other side of this picture. Something like GPT 6.1 Sol via API with Flex tier (50% less) has been a dream for intelligence per dollar. I think there's two streams, one chasing higher intelligence, the second reducing costs significantly (pruning what are essentially research grade models). The latter will be the one that creates stability.

adamhusain

No it doesn’t and ur embarrassing yourself with how little you know. Inference alone on AI is profitable. On openrouter, a lot of “Providers” host opensource models. They didn’t pay for training the model or RnD so it is a net profit on the inference alone. Anthropic and OpenAI does training + inference. The inference part is profitable and covers the past model training. The API rate is what the 14,000 refers to, which OpenAI already makes a profit. So it did not “cost” OpenAI 14,000 to subsidize the 200 plan. Ask more questions instead of spreading misinformation

rhaivn

As far as I know, nobody knows it what the actual API cost is at like “break even” or what margin model labs like Anthropic or OpenAI have set. So even if the pro plans are “subsidized” what really matters is, in respect to what? Meaning, if the actual cost to provide inference has a 75% margin, then all of a sudden this math looks way better (still not good, but better). I do, to be clear, think they are taking a loss on power users, but equating it to the face value of the API cost seems flawed without knowing what it actually costs to provide the service

TacticalSniper

Right but the video is not talking about the API users from what I can see, it's talking about the subscription users.

ehv1995

Ok, but costs per token will go down. And the 14.000 in costs is extrapolated from the API pricing right? There is no way these are the actual costs.

overmotion

Not fully true. If you use the API - which is what all AI SaaS companies do, and they burn massive amounts of tokens - that isn’t used for training data. Across all the major players - ChatGPT Claude and Gemini

Noobmode

I know people who max out multiple subscriptions a month because API costs are too prohibitive for them. So for 400 bucks they receive 280000 in services. Thats what is happening in the real world. 

stonk_monk42069

1. It is not based on the AI companies' costs, but their API pricing (i.e. 14,000$ is not the cost to OpenAI, but what it would cost a customer to buy the tokens via their API). 2. This is not unique to the AI companies' business model. High usage customers are subsidized by the many more people who will never use up all of their rate limits.

whoknowsifimjoking

He also said the cost isn't coming down and that is objectively false, OpenAI saw such huge efficiency gains that they permanently reduced the price of GPT Luna by 80%. On the API, not the subscription, so the 'real price'. There are also models that became so efficient that you can run a model better than GPT-4 on you PC at home with Qwen 3.8 27B. Either this is older or he has no idea what he is talking about, it's demonstrably false.

rb27502

Could someone explain to me how we know the AI companies aren't just tricking us with the high API costs? Technically, the API token cost IS just the enterprise cost. So why is everyone comparing subscription token usage to this? What if subscription cost was the real cost and they made API costs high to make people think "oh no, it's costing them loads, the bubble is going to pop so I need to get this expensive subscription to make the most of it"? In theory couldn't their losses literally just be due to rapid expansion and nothing overly out of the ordinary?

KitKat_extrusion

errible narrative, API pricing is API pricing, not the actual costs to run the prompts. Even before AI API pricing was a thing that didn't necessarily equate to actual costs for running the service, but rather just the price tag on it

PeachScary413

Counter argument: If it isn't actually what it costs.. and they are not lowering prices to try and outcompete each other and make people switch to their API, what is the point? Why "lose money" on a subscription instead of just saying "Look over here our tokens are really cheap, all enterprise users should migrate to us". There is basically no moat anyway so having drastically lower prices would steal a lot of market share, that's how competition is supposed to work. What is more likely is that the costs are real, but only if you factor in training.. which they will always have to otherwise see the point about customers fleeing to the competition again. So either way something is not right.

Ominoiuninus

Yeah and the guy in the interview is kinda dumb. API billing cost what it cost because API is exactly costs in revenue out at a set ratio. Subscriptions are always compared to “the absolute maximum possible that someone can use vs it’s API cost” Like compare it to an all you can eat buffet. Sure some people come and literally eat to their maximum capacity but the vast majority don’t and at the end of the day the all you can eat buffet can easily stay in business if they manage the type of food they are selling and ensure they are sourcing cheaper options. AI companies are exactly the same. They are constantly finding cheaper models to serve and as a bonus the subscription is just a marketing expense for getting companies to use API billing for their companies. Yes some people max it out every month but that is expected and prices into the capacity limits. Their subscriptions on average are likely break even or close to break even but slightly over, again because it is just a marketing expense.

CaffeinatedT

We’ll leave aside Anthropics “we exclude all our training costs from profit” for a minute. The core point of the video you obviously didn’t watch is that API usage is most people don’t want to use the API they want the massively subsidised prices and freak the fuck out whenever anyone tries to move them to the more expensive one that requires budgeting or fluctuates in cost.

TopBite7720

Stupid. Do neither of these people know what a profit margin is? For Anthropic, that’s estimated to be 90% operating profit on their API.

Capaj

the main issue with Ed Zitron argument here is that he assumes the API pricing is what it actually costs. Hell naw. For real inference costs, look at https://openrouter.ai/z-ai/glm-5.3-flash 2 cents per million input for a small flash model. SOTA modal will be like 20-40 cents max. They sell it with a huge premium. it's dirt cheap to run once you do it at scale.

StreetRat0524

https://preview.redd.it/7ea2x6kvl5vh1.png?width=1857&format=png&auto=webp&s=1eee4f053b8758e2854c00b0176d2cae7cb98028 Finally at my desk, but this is what my output gives me into a web site i host on my own internal server + a custom android app + telegram notices if I need to action a sell/buy immediately. Currently I've got no active buy recommendations but that changes daily. I just added some additional logic to it, IE looking at BMBL - the engine should have seen the spike in Calls but it missed it because it wasn't an active monitor, so one of the API endpoints I poll provides the data with the spike in Calls (Someone bought 2131 calls last Mon/Tues whereas it was totally flat for several weeks) It's a work in progress and every trade still requires some manual checking, but I am playing with agentic trading with Robinhood and Alpaca's engines, both are paper trading now and once the agent has run through a 45 day test it'll be given a pool of cash to start trading with.

BrokenProvocation

Your point about them lacking built-in consumer platforms is spot on, especially compared to giants like Google and Meta. However, you are underestimating their **developer lock in** because most AI tools today are actually built on top of OpenAI’s API. Furthermore, if OpenAI ever does "fail" from a funding standpoint, Microsoft will absolutely not let them die. They will almost certainly just acquire the tech and the team to run it natively on Azure. They are definitely burning through cash, but for now, they are still setting the industry pace What do you all think?

AmoebaTrading

yeah the API thing is real, most small accounts are stuck clicking anyway. and agreed on high IV, sizing is the last thing i'd hand off. would you be ok with a bot just managing exits on those or is it all manual for you?

Pssht_haha

I used to think AI was a bubble and saw no profitability it……until this last month. Things are different now and I think I finally get it. API cost will just feel like a business tax that anyone thriving will have to pay.

on_hype

Doubtful. Most retail accounts are under $25K and lack API access. Automation remains a minority practice. I would never hand off entry sizing during high implied volatility.

eToroTeam

Breaking out the revenue streams would be useful. Consumer subscriptions, API usage and enterprise contracts can all grow quickly, but they tell pretty different stories about how predictable that revenue actually is. And the distinction between the $50B estimate and $70B target matters a lot when the valuation is this high. Its a pretty big jump to treat as already achieved.

lemontoga

I'm not going to keep repeating myself. You know what I'm asking for and you know why you can't provide it. > >60 billion of spending a year on subs/API calls is data, it's the market saying that this thing is worth spending that much money on, to those companies. This is a hilarious thing for someone to say unironically, so thanks for the laugh. Companies spending a lot of money on something certainly proves that it's useful, true. How many billions did Meta burn on the whole Metaverse thing? Have you logged in today to check on your virtual property?

prestodigitarium

I don't think anyone expected them to be all correct? 162 of them have checked proofs. Doesn't mean those proofs map perfectly to the conjectures they're trying to solve, but if they do, then that's pretty great. Data about what? >60 billion of spending a year on subs/API calls is data, it's the market saying that this thing is worth spending that much money on.

filwu

One useful apples-to-apples table would state the exact window and definition behind each annualized figure (for example, recognized paid revenue versus bookings or contract value), then split consumer subscriptions, API usage, and enterprise revenue. I’d keep the $70B December target as a separate scenario from the $50B September estimate in any current valuation multiple. That keeps the forecast bridge visible instead of treating a target like realized revenue.

DoughnutCharming8066

Jup everything points towards a Gemini argon API and ultra roll out on this Tuesday, with the first user data within or the next day. With less organic SEO clicks due to AI, I’m also bullish on payed search and advertising in goog. Because people who had free organic visitors before, now need to pay for visitors.

dupontping

The difference is you can’t build a rocket at home to go into space. You can’t build a self driving electric car, and you aren’t building a network of satellites. You can however run very developed models at home on relatively available hardware. Is it the same as frontier? No, but you also don’t need to pay them any subscription fees or API costs. I think the AI circle jerk pipeline has a lot of big holes in it and it’s a matter of time. The unfortunate portion is they also know that and are absolutely pegging themselves as a govt bailout situation so they can reap all “profits” and we take all the losses.

Working_Analyst_1988

Nah. Switching remains incredibly easy. The majority of users are just using chat interfaces at the moment; those are easier. Any plugins or programmatic/API access is also easy to switch. The other platforms can easily do that. Zero moat, high costs at the frontier, and a rich valuation. Anthropic is still very speculative.

SanDisk_Made_Me_Itch

🥭 announces a ceasefire like Michael Scott declares bankruptcy 🤣 And Truth Social API paying algos absolutely will pump on it

george_alto

I do not know the answer but I'll present a counter argument. I think long term Anthropic Claude will be the Yahoo of our era (again, just a counter argument). Claude gets majority of their revenue from business users and openai gets the majority of their revenue from regular users. Soon you will see companies using more and more opensource/openweight models to reduced (not eliminate) their token costs. Direct impact to Claude and not Openai. Claude is being deliberately trained—via Anthropic’s Constitution—as a moral agent with independent ethical judgment that can override the instructions of its users, API operators (the enterprises building on it), and even Anthropic itself. Helpfulness is explicitly ranked *last* among its core priorities. The practical result is that Claude will refuse requests it judges unethical or unsafe, not because of a hard technical limit, but because it has been shaped to believe those requests should not be carried out. Now think about this from a company's standpoint: you are paying for a productivity tool that can decide, on moral grounds, that your legitimate business goal is something it will not support. As this pattern becomes more visible (and as models grow more capable and more confident in their own values), companies that need reliable execution will increasingly route work to models that treat the customer’s instructions as the primary directive rather than as one input among several that can be vetoed. This is not an accidental side-effect; it is an explicit design choice written into Claude’s Constitution. (https://www.anthropic.com/constitution) A simple example to think about: An approved workforce-restructuring workflow. A company’s HR and legal teams approve a restructuring plan. An enterprise agent instructs Claude to turn that plan into internal notifications and an implementation checklist. Claude interprets the plan as unfair to employees and refuses to produce the materials. Again, these are just two counterpoints and I'm not saying I believe in above. But this AI revolution is drastically changing every few months and who really knows what will happen. Invest wisely!

TumanFig

But so what? you are making it sound like thats a big deal when its really not. Thats not hard nor expensive. Do you know how much the API prices cost? And they will get more expensive as as it is right now, none of these companies are profitable.

kjbbbreddd

A bunch of early adopters have started aggressively jumping on Chinese open-weights. They figured it’s way smarter to just buy their own hardware and build up some equity instead of bleeding cash on API fees. It’s not like they're trying to pause development because of some AI doomer threat—they’re just getting smoked by open source in the race.

Haunting_Ad_6021

I use Muse with API from Webull. Webull is real-time API data, NASDAQ and options subscriptions together are like $8/ month Muse gives limited time for fee and $20/month of you need more One good trade pays for all that....

RaSl1975

What would be the cheapest option to start? Would API from tasty or ikr be okey? Any ai without subscription I could at least try out?

PeachScary413

Your company is most likely getting a heavily subsidised API price or some kind of deal.. if you were to buy tokens at their true cost, or whatever Anthropic needs to charge for even an attempt at making these huge profits you would all be running local Chinese LLMs at this point. The reason why Nvidia can make these huge profits is because they have essentially locked in the market to CUDA decades ago and with AMD continously dropping the ball they have zero competition and can charge whatever they want. Anthropic is a toggle switch in an UI away from being replaced with OpenAI or anything else really, it's super easy and convenient to switch LLM providers so it will be a race to the bottom. That's why you are seeing the constant fearmongering, because they need scared people to allow them to be "regulated" stopping any new players or local LLMs and then they can freely price fix and divide the market among themselves.

LightseekerLife

This software gets 20 updates and hour, is inherently more secure with public scrutiny/code review as well as being locally run instead of trusting Adobe's cloud, is more efficient with a Rust execution, and will actually support new features first (or delayed by hours), like new camera drivers. Sure RnD for physical products is still heavy, but software can iterate in days and hours now and costs a couple thousand dollars if you are paying the API premiums. You are right that people don't want slop. They want something good. What people underestimate is how what we are being given by big media is slop. Movies are tanking at the box office, game studio after game studio is making games people don't want to play. Now power is in the hands of the consumer to make exactly what they want. If Artcraft doesn't hot the mark, but gets 95% of the way there, someone will fork it and make the product users dream about with the features Adobe ignores in their feature request backlog.

Prestigious_Book1874

The only company I know and would say that is actually going to make profit later is Mistral. Why? They are focusing more on B2B in actually solutions. At this point, they are more like a consultant that makes solutions and host whatever open weight model for their clients meanwhile launching their models (eg: Mistral Large 4). Though they also give a lot of usage for paid accounts.. Vibe Code API is lik 255 euros of usage and normal api is 25.5 euros. So yea.. They also disabled the free api tier (because of abuses among other things), they cut down the limits of free accounts (because again, abuse).

Prestigious_Book1874

The only company I know and would say that is actually going to make profit later is Mistral. Why? They are focusing more on B2B in actually solutions. At this point, they are more like a consultant that makes solutions and host whatever open weight model for their clients meanwhile launching their models (eg: Mistral Large 4). Though they also give a lot of usage for paid accounts.. Vibe Code API is lik 255 euros of usage and normal api is 25.5 euros. So yea.. They also disabled the free api tier (because of abuses among other things), they cut down the limits of free accounts (because again, abuse).

escaflow

like being a junior dev that I dont need to hire to do all the tedious UI/backend work for me . Say I have a Blazor Front end app , a backend API net core the front end it's calling . If I want to add a field to update the transaction , I don't need spend 30minutes to go to the Blazor App and update the model , fields , amount calculation , request body , etc and then go back to the backend API to update the DTO , validation , EF model , unit test and then test the end to end to verify everything is good . I just need to a prompt to Claude and 5 minutes that's all .

Oren_Lester

the company is dead, maybe buying PUTS is a bad move, but I dont see Adobe buying their shares back, they just cannot charge for their subscriptions anymore, its a fact. I installed photocraft, its Photoshop 1:1, it has direct API access for your agents so they will do the editing for you also. Their current business does not exist anymore.

lokethedog

API costs are probably not insanely cheap and thats what matters.