API

Last_Iron1364

There is a further problem with providing inference which people don't often address and it is estimating service demand. If you purchase too little compute, then you either have to pay spot prices for further compute and the margins for each additional customer collapses or becomes outright unprofitable. Alternatively, your rent too much compute and then the service is unprofitable on account of the unrealised revenues and high overheads. The token pricing you have cited is true if a customer pre-pays Anthropic for the tokens but, if they are simply providing API access then their capacity accurately estimate request volumes becomes the make-or-break of their business. Moreover — if the existing neoclouds are any indicator — providing GPU compute is gruesomely unprofitable. This is predominantly because the economically useful lifetime of GPU hardware, as a consequence of component ware and electromigration causing increasing errors plus Nvidia's rapid release cycles, is approximately 2.7 years (epoch.ai which comports with my own independent analysis) which means they have to earn back their costs before they become unprofitable a continue running; a brutal depreciation schedule.

Vlyn

We had heavy monthly spend on Claude (it really got out of hand), so I've been pushing towards using DeepSeek v4.1 1017. Switching one colleague over to it lowered their monthly spend to one tenth (and overall over multiple colleagues it's even one twentieth based on cost per billion tokens). And that's compared to Sonnet 5.5! Not even talking about Opus or Fable here. DeepSeek is so cheap, you can run it all day long and still use less than you'd use in an hour of Sonnet with enterprise API pricing (all of it of course hosted with trusted providers, so all of it runs in the EU). Sonnet 5.5 isn't good enough to one-shot solutions either, so for the price of it DeepSeek or other cheaper models (like GLM 5.3 Flash) can iterate several times and still have less spend.

MDInvesting

It’s a joke. API credits are also being restricted.

stonk_monk42069

They earn the majority of their revenues from their API, not subscriptions.

DLRevan

It makes you more efficient (or makes you feel like you're more efficient) but what are the outcomes? Enthusiasts are building their own personal apps, but this has not become a culture shifting movement like how smartphones were. On top of that, the vast majority of such users are using free models. And would you pay for your "efficiency" if the product became vastly more expensive? There's so many layers of discounts before you get the Claude you are using even if you're on pro max. Something to the tune of 50x, and that's just based on their own API costs. Which right now, folks are arguing if even that is profitable. You should reevaluate who has their head in the sand. The technology doesn't need to be "bad" for it to be totally financially unviable.

FragmentedHeap

Yeah, AI Labs figured out that if you destill a big frontier model into many tiny expert models, and you put an API Router in front of them and caching layer and inline AI in that api layer it can intelligently decide where to route requests based on context/cache pinning and make requests sprawl out of cheap smaller models. A big model that knows everything is really only useful for training smaller specialized models, very inefficient to run inference on the big model, much more efficient to train thousands of smaller models and use intelligent routers/cache engines.

WockySlushie

That's because their *system* is walled. The AI itself is not approved for PII, the enclosure it is in is. They previously did the exact same with other AI providers. It's all just API usage.

Electrical-Fix-7694

Good catch on the credits question. Most companies treat promotional credits as a reduction of revenue, not gross revenue with an offsetting expense. So if they gave you $100 in API compute, that $100 likely never hits the revenue line at all. The real thing to watch is whether they're classifying free credits as marketing spend in SG&A while counting paid usage at full gross revenue, which would make the revenue growth look stronger than the actual cash coming in.

NeedMoarLurk

They're on a subscription not using the API. It is much (much!) cheaper, but you have usage limits on a rolling time window and a weekly maximum

DLRevan

US companies also won't spend 10x more on something a human can do, even if the human is slower or has a less broad skillet. The vast majority of even enterprise customers are paying not API prices, but subscription prices by stacking multiple accounts. At present, anthrophic's subscriptions subsidize the costs versus using the API by some 50x, sometimes more. Do stock traders and market analysts actually know and understand how the product is being used and served? No matter how you slice it it's not sustainable. The product in question is either so cheap it's distorted demand on a scale never seen before. Or it's so expensive, you could literally save money by dumping the AI that produces the output of 10 people, with more than 10 people. As much as 100 people, in the case of some workloads. There's possibly just a very boring answer to the AI bubble. It doesnt matter if humans or AI is better at a given job. AI is just not efficient and not sustainable. I should add that we're not even talking about the actual gains by clients and society downstream beyond business demand, which is technically still just the result of subjective business decisions. There's no evidence of actual benefits...at least not yet.

yatv

Okay… so you haven’t even used it personally but anyway that’s great, I use Opus and Fable for my personal work, I agree it’s better, I already said Claude takes the cake in terms of model quality. But the money in AI isn’t in appealing to individual users / B2C paying for subscriptions, it’s in enterprise. B2B customers want the right balance between model performance and low token costs, and that’s where Google has positioned itself to dominate the most commercially viable segment of the market. Enterprise customers pays significantly more through API usage then individual users like yourself do. I’m a software engineer at a prominent SF based startup that was recently valued at $279 billion in a Series B round. We use Google’s models for all consumer facing tools on our platform because they allow us to offer significantly higher usage limits at a lower costs + the users operate within a narrowly defined set of use cases, so we don’t need the most sophisticated general purpose model. We need one that performs reliably within those constraints while remaining scalable.

LeopoldBStonks

Yes I know open code is a dog shit harness, but you can add a layer to it of your own software, I did it two weeks ago, blamo, my Nvidia Jetson can code and modify word documents locally or via a DeepSeek API.

Basic-Initiative-298

Lol perplexity is a crappy LLM with a search API rag. Users like you make up maybe 0.0000001% of AI token usage.

A_lonely_ds

But they arent really. This notion that the model is all that matters needs to stop because it prevents meaningful discussion. We always knew that intelligence would become a commodity, so thats not really the playing field. So consider a few things: 1) when normalized by intelligence, the value prop from open weight models kind of evaporates. In many cases OAI is far more efficient with some of their models than what is coming out from deepseek, moonshot, etc.. Anthropic has positioned themselves as a premium product however, and people are happy to pay that it seems. But open weight labs have not found some secret sauce that allows them to serve models far more efficiently. 2) Hardware and infrastructure remain the primary play over the next year or so. Securing compute so aggressively means that as demand continues to increase OAI/Anthropic will be the ones best positioned to meet the demand. Enterprise customers, just like with any service, pay a permium for uptime and reliability as well as capacity availability....also means: 3) Enterprise is VERY sticky. Its why copilot is such a major player despite being objectively a pretty poor harness (although its got much better the past few months). Most large companies will be accessing US models thru copilot, some may go enterprise ChatGPT or Anthropic...but no enterprise is bringing a smaller harness in house. As for API, same kind of applies. 4) We're now entering into the 3rd/4th wave of pricing structure. Where you pay for outcome, not for tokens. Wave1: free Wave 2: Sub based Wave 3: Token Based Wave 4: Outcome based/Unit of work based Subs/Tokens wont go away, but increasingly you will start paying for an agent or fleet of agents that do *something* its why OAI just changed their plan structure with the introduction of Dots. Its hard for a company to justify $2000 a month on 'tokens'...but if you have a Call Agent that handles one call every 10 minutes 24hrs a day...and say costs...$3/call...vs $10/call for a human...Anthropic or whoever can charge $4320 a day for that agent...its still $10k cheaper than a human. Now expand that to robotics, etc... 5) And what I think is the most important...people seem to underestimate the TAM here. The TAM is so huge that in a number of years, yeah, OAI/Anthropic could be worth trillions...you could also have second wave players also worth hundreds of billions....I dont think people realize how much money is really on the table *if* AI can convert to real world economic impact. Which I think we are finally starting to see in a meaningful way over the past 2 months.

SpeedflyChris

So is their business case "We would be profitable if we only had our business users that pay enormous API rates, and if we also stopped training new models, in the full knowledge that doing so would cause our Chinese competition to absolutely eliminate our frontier model lead inside six months"?

SpeedflyChris

> With little warning, Anthropic switched enterprise to token based billing. Suddenly, companies were acting like the sky was falling. User ran around screaming that they lost their entire years budget in four months. It's coming to their personal use accounts as well - the usage limits get a lot of complaints in the Claude sub but if you get the API-equivalent cost for the tasks you give it or your usage over the last while then it's absurd the amount of usage they let you have compared to the price you pay. I got a 20x account for a few months to help build some personal projects of mine, and last month, when I pretty much used up my limits every week, the API-equivalent cost for all of my tasks exceeded $8000. Given that I paid Anthropic a little less than 2.5% of that after VAT, I can't imagine that they made a profit on my account. When I run things via Openrouter or similar I *never* use Anthropic or OpenAI models (I might make an exception for GPT-6.1-Sol, because that model is genuinely pretty good for the money). Paying Anthropic or OpenAI $50 for a task I can have a Deepseek or Qwen model do just as well for $2 just doesn't appeal.

Altruistic-Package11

Exactly this, I'm also a software engineer and we've been swapping out expensive frontier models for more specific ones, like JEV or some of the open weight ones where it makes sense. Or, instead of using the most expensive model to do dumb shit like determine if a phone call is inbound/outbound just look at the upstream API provider's inbound/outbound flag.

SoggyMattress2

They don't have a direct to consumer model, the average person is ambivalent towards or hates LLMs, they'll never pay. Less than 0.2% of their revenue is individual consumers. They are hoping (wrongly) that LLMs will become good enough to replace workers - at that point the fucking rocketship takes off cos every single business on earth would buy that. They've expended the current TAM - it's basically just tech and then anyone dumb enough to try and roll out AI services at API cost, so revenue will flatten off from here.

howudothescarn

Sorry but most US companies will not use a Chinese model. Definitely not on API - maybe if they are willing to fork out millions to host their own model. Even then probably US models.

SpeedflyChris

>Why would people want to use the 3rd or 4th best AI client? Because it's "good enough" and cheaper. If you look on Openrouter, to see what businesses and companies go towards when they're definitely paying API rates and not just burning masses of gullible venture capital through loss-leader subscriptions (the usage limits on both are *hilarious* - I burned the equivalent of $8000 in API usage last month on my £180 claude plan), the cheaper Chinese models have gone from being a single-digit percentage of usage last year, to more than half this year. When I run tasks through Openrouter (which I do regularly), why would I pay OpenAI or Anthropic $50 to do something, if a model from DeepSeek, Qwen etc will do it for $2, and both produce code of a similar quality and meet my needs? You can see this with the recent releases from both OpenAI and Anthropic - OpenAI recently put out GPT-6.1-Sol, which has a big focus on "good enough" performance at low cost, and Anthropic recently put out Haiku 5.5. The reason that both OpenAI and Anthropic are ultimately doomed to bankruptcy is thus: 1- They have *absurd* levels of financial commitments, and in order to meet those commitments they need to stop losing billions of dollars every year and start making massive profits, *now*. 2- Training their models is incredibly expensive, and the "moat" it buys them is extremely temporary. They can't afford to keep spending on training the way that they have been, but if they stop then their revenues will fall off a cliff in short order as the Chinese and international labs catch up and eat their lunch. The best open-weight models are less than a generation behind the current frontier models, maybe 4-6 months behind. If Anthropic and OpenAI stop spending like money is no object on training, then inside a year cheaper alternatives catch up and there is suddenly no reason for companies to spend the higher prices they demand. Meanwhile if they do keep burning billions of dollars per month on training, as the models advance there are increasingly few tasks that actually "need" the very latest and greatest model, so the market becomes increasingly price-sensitive anyway. Honestly if anyone is considering buying into this IPO please contact me before you do so, because I have a huge portfolio of investment-ready bridges that you will *not* want to miss out on.

int122

Stats from companies are hilarious. 45 minutes weekly saved time to merge code down by 50%, another estimation API migration down from 231 to 13 days, pure estimation to look good on paper And looking at my company, estimations are really bad most of the time. Like nobody know cost or doesn't want to tell? How much more money they earned thanks to AI? These are big tech, rapid growth, what if doesn't continue like that. My favorite areas are science/health. Wouldn't be surprised there will be best usage, financing from state and moving forward rapidly in research area, better than saving half an hour weekly for one salesman.

waitmarks

The S-1 shows finances through june 2026. A couple things happened around that time that would make it look particularly good for them financially. 1. They rug pulled big corporations on token costs earlier in the year which came to a head in may. Before, they allowed them to use subscription pricing and then changed it to force them to pay API costs which blew out a bunch of people's token budgets. 2. SpaceX gave Anthropic a discount for using the Colossus data center during may and june as an introductory price for those 2 months. They pay full price after. So, this is basically the rosiest picture they could paint ending the reporting period in june.

Eresbonitaguey

Open models only lag the frontier by about half a year and some other company will sell you API access for peanuts compared to Anthropic. They’re cooked.

Free-Pop-6773

Je vois l'intuition, mais trouver un RCE et vendre une plateforme à un CISO, ce sont deux métiers. Snyk, Semgrep ou Wiz scannent déjà du code, et ce qui coûte cher c'est le triage puis le patch dans le SI du client, pas la découverte. Si tu veux jouer le thème, regarde plutôt ceux qui ont déjà la distribution, Palo Alto ou CrowdStrike, que les labos qui finiront sans doute par vendre leur moteur en API.

BlueberryWorried6493

>You cant be spending that much when demand isnt there yet What makes you think demand is not there? My company just doubled our API token budget, after already doubling it 3 months ago

niaqr

What API do you guys use to see futes

huan0462

SpaceX is securing $40 billion to push the frontier of compute, and you couldn't spare two cents of API credit to run this through a model with more than three working parameters. "Not rockets. Not satellites. AI chips." Did you prompt a lobotomized free-tier bot to write LinkedIn broetry for illiterate day traders? The irony of gawking at high-end silicon while outsourcing your post to a bottom-of-the-barrel LLM that defaults to cheap tricolons and manufactured engagement bait is painful. The industry is buying chips to produce actual intelligence. Have some self-respect and stop using the discount bin version.

Arrowhead_Pride15

Reddit sells digital billboards on the 6th most visited website in the world, and since they don't pay any of us or the jannies they have 90% gross margins selling digital billboards and 100% profit margins selling API keys to OpenAI, Gemini, and (soon.... probably) Anthropic and the rest of them. Their capex and their debt are basically non existent, the market has been super pessimistic on RDDT but like, here we all are, commenting, giving Reddit AI training data for free.....

_AT198

Rddt and Iren are new positions for me. Took a risk opening before the biggest catalyst week of the quarter. Rddt is long term. They google deal is up in 2027 and both rddt and google know how valuable the API’s are. The concern about Iren is how much is priced in. They deliver to Horizon to MSFT, but not sure what else is left to give it a boost other than the valuation being strong. What’s your thought on both?

Whiskee

No it doesn't, that's just the API pricing. I promise you're not wasting $25.000 of electricity with those plans, hopefully one day people will stop parroting this idiotic shit everywhere.

cogit2

For context: Google will give you free YouTube Premium with your AI Ultra sub Google will give you 30 TB of Google Drive storage and $100 in API/console credits Google will give you loads of Google Flow (for video generation) credits) Plus... a dozen other things I can't remember. This isn't a Gemini ad It sure isn't...

X3n0bL4DE

Yeah, enterprise doesn’t get $4000 of compute for $100 though. API billing subsidizes monthly plans. They almost certainly have large margins on their API costs - and that is how the majority of enterprises have their plans set up.

Hoak-em

Kimi K3.1 just came out, it's around Opus 5.5/Astra, beating on some benchmarks (Terminal Bench 4.0, generally pretty reliable bench), usually scoring inbetween the two, far cheaper API cost as well, with really great performance outside of coding tasks as well like finance, scoring similarly or better than Fable 5.1.

qazxdrwes

It's useful for programmers, but how useful is it for the average person? Agentic AI wants to provide commands to programs and get them to work. Most companies have internal tools that can't be accessed via commands or API. Non tech companies will be slow at adoption. The question is whether the pace of the AI rollout matches the pace of demand. I have a feeling that the demand will lag severely. I think the heart of the matter is that good companies already have a lot of automation going from, provided from exact output from programs. It makes no sense to switch to an LLM when we already have existing, low compute solutions to many of our problems.

NuclearBunney

Distribution is an API key. Anthropic n co will reach mag 7 revenue faster than anything there has been is history

SentByTheRiver

No one will argue with you about it being the playbook. Loss leading has been done for decades, including products in supermarkets. You are comparing apples to oranges though. Typically you run Adobe and Autocad on your machine, it doesn't require billions in sever racks/gpus to run and you don't need to pay every time you want to run use any feature on it over and over again. You can see what nothing you're saying is actually aligning with my argument. You need to make a like for like comparison to argue against it, or something close. Google supplimenting (comparatively against AI) modest sever infra to support their money printing ad business and one time purchase, yearly licence autocad/adobe are not the same as AI subscription/API billing models.

Alert_Weird6893

this is first of the many. find next such business that AI will destroy and give it a few quarters..or years. and profit. are there any API companies that provide similar service via API or anything that can be easily replaced? maybe some cooking sites that teach to cook and charge for it?

Kind-Connection1284

I’m in tech, we spend a lot on AI tokens each month, and this is a bubble. Subscriptions are heavily subsidized, we use API tokens i.e priced closer to reality and it’s expensive AF. Management already asked us to use open weight models as default and only use frontiner ones exceptionally, as they’re too expensive

West-Structure-4030

If you build it yourself, the hard part isn't the formulas, it's getting clean financials in without copy-pasting every quarter. Excel's STOCKHISTORY/stock data types get you price but not much fundamentals, so most people end up pulling from an API or a site's export. If you'd rather skip the spreadsheet, I've been building [usstocksense.com](https://usstocksense.com) (disclosure) for US stocks: you type a ticker and get fundamentals and valuation side by side with peers, plus a screener. Still worth building your own sheet once though. You learn a ton doing it.

SpellingIsAhful

I honestly dont understand how you spend 80 billion on that. I would gues that the main spend was back end data tracking and API type stuff. Setting up a virtual world kinda seems like a layup considering that there were games like Diablo 2 doing it decades ago.

ScottieWP

Depending on your broker, just use an existing bot management service like Trade Steward, etc, to trade via API.

Zealousideal_Book_40

Problem with your estimates is you are trying to assign a dollar number per employee, when what is already happening is that the AI agents are also being placed in automatic workflows even in the most backwards companies. The real question is how much value can company get out of automation and does the automation require the llm API and does it have to be the most intelligent one? Another question is how fast the physical AI catches up with digital assistants - physical AI can be even more token hungry as it needs to evaluate sensor readings in real time, unless it's a dumb factory robotic which actually doesn't need AI at all

No_Pressure5505

Ever since trump sold off his truth social API. he hasn't given us a 2% god candle since with his tweets.

d70

i don't but here are some recent reports. all public info: * Microsoft: Satya highlighted that Azure cloud growth continues to see strong demand from AI workloads, with Microsoft 365 Copilot crossing 30 million paid enterprise seats as commercial customers scale up token usage for business workflows. * Amazon: Andy Jassy reported on AWS earnings calls that cloud growth is re-accelerating rapidly due to generative AI services and Amazon Bedrock adoption, with massive multi-billion-dollar enterprise backlog commitments moving from proof-of-concept into full production. * Google: Sundar stated that Google Cloud revenue surged primarily due to demand for AI infrastructure and Gemini enterprise solutions, with close to 90% of Fortune 100 companies now using Gemini and developer API token volume hitting tens of billions per minute. * ServiceNow: Management noted that AI annual contract value crossed the 1 billion dollar milestone, with corporate IT and customer support teams actively paying for Now Assist add-ons to automate employee workflows and resolve ticketing pipelines. * Salesforce: Executives detailed that customers deploying Agentforce directly into live production surged by 50 percent quarter-over-quarter, proving that enterprises are actively purchasing autonomous agents to handle sales and customer service. * Adobe: Management disclosed that AI-first annual recurring revenue cleared 500 million dollars, driven by corporate clients like Disney and T-Mobile consuming Firefly credits for commercially safe media generation and marketing assets. * Palantir: Reported triple-digit growth in US commercial revenue, pointing to corporate demand for its Artificial Intelligence Platform (AIP) bootcamps where manufacturing, supply chain, and healthcare clients convert directly into multi-million dollar production contracts. * JPMorgan Chase: Disclosed in earnings commentary that hundreds of internal generative AI and machine learning tools are live across global operations, driving hundreds of millions in measurable savings across fraud mitigation and automated underwriting. * Morgan Stanley: Confirmed that its OpenAI-powered advisor assistant has scaled firm-wide across thousands of financial advisors, automating research summaries and meeting prep across trillions in client assets. * Walmart: Detailed on calls that generative AI enabled teams to enrich and catalog hundreds of millions of product listings around 100 times faster than manual processes, with GenAI search boosting overall basket conversion. * Spotify: Management flagged prompt-based playlist generation and the conversational AI DJ as primary engagement levers that helped expand subscriber retention and operating margins.

hondajacka

swapping LLMs for enterprises is super easy. You just change the API endpoint. There's no moat.

ShadyShroomz

they are already at $100b ARR, & their estimated market cap in the private market is $1.5T. also inference (API & subs) are very profitable for them despite people claiming that subs are "subsidized". Their costs are in the training of new models. For reference; an 8x b300 system costs them $600k and can handle 16,000 tokens generated per second (estimated numbers, assuming that Opus 5.5 is a 5-10T parameter model with 200b parameters active). across 24 hours a day at full load: thats 1,382,400,000 tokens per day, & 41,472,000,000 per month. claude pro $20 plan gives you roughly 10m writes a month (as of now)... so a maxxed out server could host around 4,180 users maxing their $20 plan (assumption 2)... or $82,472 in revenue.. making the B300 payback - not including electric costs* around 7 months. The server pulls about 14kw, so about $1.40 per hour for each server at 10 cents a KWH. Nothing insane there. so even a pretty bad case scenario (im sure a ton of people are not maxing out their usage) - they are still making a ton of money from $20 subscribers. I know im skipping a ton of shit like prompt processing etc.. but that's generally very quick & a small % of the total usage, vs write speed.... but again this is a worst case situation where every person on a $20 plan is maxing out their usage. If we look at the price to rent a B300 at runpod, its $9/hr ($72 an hour for 8) - so even using that as the baseline (which of course, is a company who needs to make money as well, so you can assume that Anthropic is not paying that much), you can easily put 57,600,000 tokens through in an hour... which is 5.7 users monthly allowance... so $114 in revenue for $72 of inference. So again, they are profitable even at 100% of usage. Couple the profitability with the revenue growth.. and you have a recipe for a great company here... For reference some other companies revenue: • Amazon (~$716B–$742B) • Walmart (~$713B–$735B) • Saudi Aramco (~$455B–$487B) • Apple (~$416B–$466B) • UnitedHealth Group (~$445B–$450B) • Alphabet (Google) (~$402B–$445B) • Microsoft (~$318B–$331B) • NVIDIA (~$215B–$302B) So Anthropic being at $100b - but with ~80% margins (before revenue share & training) instead of amazons ~10%.... Yes, it is going to be priced much higher... $100B ARR: https://finance.yahoo.com/technology/ai/articles/anthropic-tops-100-billion-revenue-224001996.html 80% margins: https://www.reuters.com/business/retail-consumer/anthropic-tells-investors-it-will-be-profitable-second-straight-quarter-ft-2026-09-13/

sarhoshamiral

> because producing code was never the bottleneck as any good engineer will know. It absolutely was, are you kidding? If producing code wasn't the bottleneck we would not have feature backlogs. Producing code was a bottleneck, along with testing etc. > Every metric shows now that AI has had no significant impact on productivity Which metrics? My own and rest of org experience suggest otherwise. However the change wasn't just to simply ask models to do something. We had to invest decent amount on infrastructure to ensure models had gates to fall back on to and validate their work. But now that is there, we can actually have agents running 24/7 writing code. And personally work is more satisfying for me because I can focus on solving hard problems and not worry about coding the logic I came up, not worry about remembering method names, which API to use etc. Those were not the fun part of the job for me, problem solving was the fun part.

HydraMC

You don't give it your password for financial information, it's a plaid API, and in certain cases it can be read only (if you are only using it for purchase history/budgeting and not actually buying anything). Giving and autonomous agent your password/credit card info so it can purchase things on your behalf is pretty stupid though

triplebits

Subscription is profitable for them but not to the extend they want. Both OAI and Anthropic dont want competition hence they want to hoard every possible resource and that needs money. API is the price they want to charge. It is too expensive though so mid to big size companies can pay those prices. However if they provide subscription people who use them can advertise and mention to the companies they work at. Many including myself did that hence word of mouth brings bigger clients. Subscription also increase their user base which helps with funding and how much their company worth. It is their way of pulling users which also provide them with feedback and more data to train on.

cbusoh66

I got the $200K/month Truth Social API subscription for nothing Not a single fake peace deal announced in weeks

SoarInTheSky-450

Btw, genuine question. Why would they want to push API? How is that any better for them than using the apps they provide? Maybe its because I've not used the API side yet, not found a need to yet?

Realistic-Cheetah413

SpaceX is making money from starlink not AI, AI inference isn’t scalable which is why every AI company costs go up at a multiple of their revenue. It’ll be interesting to see how they hid the subsidization of their monthly plan tokens so they can count the revenue based on total tokens used at API cost instead of monthly subscription revenue.

CUbuffGuy

It's a tape change reading from aftermarket close at 8pm before overnight trading. When most of the major brokers close at 8pm, their last price reading is whatever SPY was at 8:00pm yesterday. Then overnight movement happens. Only a small percentage of brokers do overnight trading where pricing is fed to the chart you're watching. So they track the price no issue... Then when all the other brokers reconnect to have the pricing data fed back into Robinhood/whatever this is, the first reading they get was the last price at close 8:00pm yesterday. So for one tick, it shows the last recorded price (8:00pm yesterday), before updating to the next buy, which is where overnight trading is (at the present time in my example). So, this is why you often see a price jump to yesterday close, then it comes right back down. Everyone screeches in the daily about some huge price movement, when in reality it's just an old API reading from yesterday that hadn't been refreshed since the broker didn't support overnight trading.

jasperCrow

Anyone paying 🥭 $100k a month for his insider API? Plz repost here first.

Orzhov_Syndicalist

Having the best model isn’t going to be that relevant. There simply isn’t that much of a difference at top levels. The difference is user base and markets. Anthropic has a lead on Enterprise API. Those relationships and subscriptions will be their moat

LabyrinthLayers

Truth social API pump 🤝 Truth social API dump

Upset-Motor-2602

I love it. the data API alone is worth a lot for me.

PopcornApocalypse

Dystopia app. It’s an ADA accessible loophole that got a flood of new users after Reddits API token move killed all the best reader apps run by volunteer coders. (RIP APOLLO)

CBFball

Uhhhh enterprise are going to be API based and even if they’re somehow not… your point that you’re going to switch to copilot because it’s cheaper is just… wrong? Copilot is a conduit to use Anthropic and OpenAI models? It’s not “cheaper” it’s the exact same thing but now serviced not directly from the model provider?

the_infamous_walrus

They make most of the money on enterprise plans with a cost per token basis using an API key. Trust me bro moment but we and many others use agents now so we don’t actually ever have to type code anymore. I would take a paycut just to keep it.

Haunting_Ad_6021

I use Muse but any AI will work. Just ask it to screen the market for whatever criteria you want. It won't have access to real-time data but you'll get the idea. Then just subscribe to your brokers API data feed and to trade, I use webull and it's $8/month for realtime NASDAQ and opra data. The AI can walk you through the process

I_know_nothing_42

Schwab streaming API quotes are always delayed, high volume spikes in the market push it out. it can be over an hour old at times. I can tell I'm getting the stream within micro seconds of being pushed the inform, but the info sent is old.

LucaRossi0

Slap a ChatGPT API onto the Ask Jeeves website, rename it 'AskJeeves.ai', call it an 'Agentic AI Butler', and raise $50M from VC funds before lunch.

jasperCrow

Why don’t we have 1 Truth social API for WSB?

SomeFuckingMillenial

Imagine when local AI becomes capable enough for the majority of tasks and "free" for API calls. Then what do they do?

SilverJackfruit7542

If he actually wanted to execute it, the playbook is entirely doable by leveraging existing government data pipelines and financial tech infrastructure. SpaceX wouldn't have to hunt down 73 million kids manually; instead, they could build a secure, streamlined digital portal in partnership with a major brokerage or financial institution where parents input a child's Social Security number to verify eligibility against standard federal demographics. To legally bypass the hurdle of minors owning private shares directly, SpaceX could establish a master trust or corporate-backed public benefit entity that holds the equity on behalf of each child until they turn 18, entirely automating the compliance, tax-id verification, and custodial framework via API integrations—transforming what looks like an impossible administrative nightmare into a massive, one-time software deployment.

m0nk_3y_gw

The Schwab data API had a massive 0dte data issue today, but I didn't see the issue in ToS (ThinkOrSwim web and mobile). I.e. my python algo was getting SPX/TSLA/QQQ option chains where all the greeks were set to -999 if they expired today (TSLA for Friday seemed OK). They fixed it 60-90 minutes after market open. It was annoying, but I manually placed my limit orders in ToS instead of relying on the API. Regardless, do not use market orders for options, unless you like surprises Maybe schwab was displaying old/delayed data for that ticker or strike, maybe data packets were being delayed somewhere between Schwab and your network, or between your network and screen (i.e. network or display driver glitch)... but if you used a limit order for the price you wanted this wouldn't have been an issue.

SourceNo2702

This is pretty obvious with some of the recent trends with the new Opus model we’ve been seeing on the internet lately. For example, those “game merge” mods aren’t actually reverse engineering anything. They created an API which can convert collision data into a generic collision API which is usable by everything. Everything else is a simple green screen. They then made a bunch of bots to advertise the capability to get people talking about it. The only thing the AI actually does with those mods is run some test cases. You don’t need an AI to do that.

cbusoh66

Just got my $100K subscription to Truth Social API. Follow me for pre-pre-Truths updates.

callmechristianblack

I believe they represent a data security threat because there is no assurance of date l data security in they API tos. Seems to me that the real cost of their cheap tokens is the fact that your data is training the models and who knows what else

greytoc

It's not a new thing. The RH service is mostly marketing fluff what I've seen. People already do stuff like that with other brokers that offer an API.

Trey_Wingo_

You are right, i found an API i can pay for to simulate if i cut every trade at 3 minutes what my P/L would be, results to come soon.

OvertaxedOne

This is certainly true but it's also not where a company like OAI is going to get the revenue necessary. People sending in simple prompts for their home use are NEVER going to pay what it takes to have a frontier model be financially successful. In fact, the sub customers (personal) are really a loss leader for these companies, what they want is API business (IE, businesses), that's where they can charge the big bucks. Problem is, those same big companies that are the real target market for the frontier labs are the same companies with a large IT staff that can easily setup local inference. Or model routing and decision support tools that make use of open models where they can and only escalate to the frontier as necessary. The exact target market is the same market that can and will easily optimize out a lot of usage.

Thistlemanizzle

At this point there is a lot of money being spent on tokens at API prices. It's not "free" anymore. Demand will only increase but...I have zero idea how to invest around this concept. The valuations are hard to understand.

3141599

Assuming that's true (I need proof), you can always automate it with a simple script and the exchange API, avoiding registering your order on the exchange. Secondly, apparently not using stop losses didn't work out either. And now the OP has lost the entire account.

Bmoses99

Sheets is not the way. Pull the data through an API into Python, or plug it into Claude and ask it questions. I use FMP for that

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.