Anthropic

The sector already invoices 80,000 million a year, but OpenAI and Anthropic take 89% of the income

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Everyone wants to get a piece of the AI ​​pie, but the reality is that the pie today belongs to two companies: OpenAI and Anthropic. This confirms it an analysis from The Information in which the income of the 34 most relevant companies in the market today has been analyzed. The accounts are beginning to be striking, but so is the reality of this new technological duopoly. The sector doubles income as a whole. According to the data collected by this means, these 34 companies have an annualized income of 80,000 million dollars, about 6,600 million dollars per month. That represents 112% more than six months ago, which means that these companies have grown more than double in that period of time. The most relevant fact is not in fact that. But in reality Anthropic and OpenAI are the ones thatthey win. That figure would be promising if it weren’t for the other major conclusion of the study: 89% of that income goes to just two companies: Anthropic and OpenAI. The other 32 share “the crumbs”, because almost 9 out of every 10 dollars in income goes to the accounts of these two new technological giants. This is generative AI. The analysis published by The Information includes the 34 main companies in the generative AI sector. Therefore, hyperscalers (Amazon, Microsoft, Google) or other large technology companies that participate in other areas of the industry. The report is therefore especially striking when it comes to verifying how much these companies are earning, and the reality is clear: they have grown very, very quickly. But (I). We have two big buts. The first: although both Anthropic and OpenAI are growing significantly in revenue, it must be taken into account that not all of them are for these companies. Anthropic has to give up some of that revenue to both Amazon and Google because they resell their services. OpenAI must also share 20% of its revenue with Microsoft until 2030, which means that this year it will have to pay about $6 billion. Companies have turned to AI, and the big winners are both OpenAI and Anthropic, which has accelerated exceptionally in 2026. Source: VisualCapitalist. But (II). The second but is even more important, and is that of a reality that continues to be overwhelming: these companies continue to spend much more money than they earn. OpenAI itself has estimated an expense of 600 billion dollars in computing capacity until 2030, and only in 2026 are their losses expected to triple to 14 billion dollars. It doesn’t matter if you win a lot: you keep losing even more. With Anthropic there is no recent spending estimate data, but the company itself has a projection of a cash flow of $17 billion in 2028. That is not the same as profits but it is a clear indication of when it expects to stop losing money. The important thing here is that this is an estimate. It could be fulfilled, but it could also not be fulfilled. The little ones grow. Three of the best-known AI startups have crossed the barrier of 500 million annual revenues since December and they now join Cursor, which achieved it last summer. These are Perplexity, ElevenLabs and Cognition, which demonstrate that they are already capturing part of a market that does not stop growing… and spending. But the big ones don’t stop distancing themselves. Although all of these startups already have an important dimension, Anthropic and OpenAI are at another level. Both have grown exceptionally and in recent times we have seen the takeover from Anthropic to OpenAI, which already has managed to achieve in market valuation. The creators of Claude were valued at 380 billion in February, but the success of Claude Code and his models in business environments has caused its price to skyrocket. The company plans to raise tens of billions of dollars this summer to reach a valuation of nearly a billion dollars. Stock market IPOs in sight. Both OpenAI and Anthropic are preparing their respective IPOs, and in both cases they hope to lift each about 60 billion dollars from investors to become companies right off the bat with market capitalizations that could be around a trillion dollars. It is an extraordinary figure, especially considering that at this time only 13 companies around the world they exceed that figure. In Xataka | Google and Amazon Just Invested Billions in Anthropic: It’s the Biggest Clue About Who’s Winning in AI

Anthropic does not offer its services in China. So China has invented a black market for Claude tokens

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Claude has become in the most desired model by the most demanding developers and engineers, but it is not available in mainland China for regulatory and safety reasons. The demand there remains notable, and to satisfy it, an underground token economy has emerged that allows local developers to access models such as Claude Opus 4.7, avoiding all the measures imposed by the blockade. No paying with Alipay. One of the measures that Anthropic imposes to prevent the use of its models in China is to only accept international credit cards such as Visa or Mastercard. Their payment gateways reject local payment methods like Alipay or Wechat Pay, giving Chinese users a first and important hurdle. One that they have already overcome. Virtual cards. What they are doing in China to overcome this problem is using virtual credit cards (VCC) like DuPay or WildCard. With these services it is possible to obtain Hong Kong or US credit cards financed with cryptocurrencies or through local transfers. This makes it possible to deceive the billing systems of Anthropic and other companies that offer banned services to Chinese users. SMS verifications They are also solved through “SMS farms” that also avoid this problem and even others such as identity verification that also have implemented in Anthropic. The “Transfer Stations” arrive (中转站). Another problem is that even overcoming that first barrier, latency and micro-cuts mean that the use of Claude in China is affected by continuous connection problems. To avoid them, so-called “Transfer Stations” have emerged, which are nothing more than servers that act as a bridge between foreign servers and Chinese users. These gateways receive requests from China and forward them to Anthropic servers as if they were coming from an authorized location. The latencies are also relatively low, which means that for Chinese users the experience is basically identical to that of a user in the US or Spain, for example. These stations are publicly known and do not only appear in listings on GitHub: there is a ranking with the best. Claude is almost free in China. The surprising thing about these methods is that they don’t just give Claude access in China: they do with ridiculous prices which can be 10 and even 5% of (growing) original price of the service thanks to those transfer stations. The question, of course, is how it is possible to access Claude at those prices. The almond tree trick. Thanks to the transfer stations, developers can access Claude at a price of 1 yuan for every dollar of tokens, or in other words, up to a 90% reduction in the official price. It is something that is discussed publicly and that makes it clear that several methods are used to achieve this: Mass purchase of capacity, Use of accounts created with stolen or fraudulent cards, Use of promotional credits, and A simple hook: providers lose money with Claude, but they manage to attract developers to whom they then sell more profitable local models like DeepSek. Am I really using Claude? One of the growing risks in the cheap token market is direct fraud. Some Chinese resellers have been caught red-handed offering what they call the “Claude API” when in reality what they were providing were much cheaper and mediocre models. For a user to detect this type of deception it’s very difficult unless you are working with complex tasks or you have already used models and know more or less what to expect from them. For victims, the effect is clear: they believe they are paying for the intelligence of Opus 4.7 when in reality they are receiving answers from a low-end AI model. Goodbye to privacy. When a user purchases tokens at one of these transfer stations, they completely give up the confidentiality of their data. All queries and responses end up passing through the intermediary’s servers, which can and apparently does use them to sell them to AI companies that use them to post-train their models. So everything they do and say when using these models is filtered and used as training data without the user knowing. A double business. For these providers, this business of reselling conversations is especially interesting in the face of the famous “distillations” of US models that take advantage of this data to “copy” the capabilities of those models and apply them to Chinese models. Anthropic can read us, but (theoretically) it doesn’t. It is true that the conversations we have with Claude (from Spain, for example) are also stored on Anthropic’s servers, but the company makes it clear in your privacy policy that does not use that data. In fact, we can even explicitly prohibit the company from using them in the privacy settings of Claude’s account. The game of cat and mouse. At Anthropic they know very well what is happening and they are trying to prevent it. For example, they have begun to intensively block IP ranges associated with VPN services or data centers known to be used in these transfer stations. Even so, Chinese providers usually respond with an “elastic” architecture that allows IPs of domestic residences to rotate, making the traffic appear completely normal. Image | Xataka with Magnific In Xataka | There is a thing called “Ornn price index”, it is out of control and it is bad news for everyone

It is called Anthropic and it is going to pay you 200,000 million, according to The Information

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Anthropic has agreed to pay Google about $200 billion over five years for more computing power, according to has published The Information. The figure would thus place the AI ​​startup as Google Cloud’s largest individual client, representing more than 40% of the backlog of earnings that Alphabet communicated to its investors last week. From commitment to commitment. A revenue backlog reflects contractual commitments already signed by a cloud provider’s customers. That Anthropic occupies more than 40% of Google Cloud says a lot about the extent to which the startup has become a structural piece of Alphabet’s business. There is also another nuance to highlight: that large AI companies like Anthropic or OpenAI still need the hyperscalers to continue growing, so in this sense, both Microsoft and Google can afford not to have the best AI models as long as they receive such an amount of income from offering such computing capacity. What the agreement consists of. According to they count In The Information, the pact, signed in April, includes massive capacity of TPUs (Google’s own AI chips), supplied in collaboration with Broadcom. However, this infrastructure will not be ready after 2027. Anthropic, for its part, not only works with Google hardware, since also uses Trainium chips from Amazon and Nvidia GPUs, playing its cards well to diversify suppliers and not depend on a single company that supplies computing capacity. The now classic circular financing. Alphabet has been investing in Anthropic for years: first it was $300 million in 2023, then another 2 billionafter 1 billion more in 2025. A few days ago we also discovered an investment of up to 40,000 million additional payments by Google, of which 10 billion would be disbursed immediately and the rest would be conditional on objectives met. In exchange, Google Cloud will provide an additional 5 gigawatts of computing capacity. This way, Google invests in Anthropic and Anthropic spends that money in Google. Is called circular financingand it is the key to how the foundations of AI are made of promises. According to account In the middle, the contracts signed between large cloud providers (Amazon Web Services, Microsoft Azure, Google Cloud) and startups like Anthropic and OpenAI already add up to more than two billion dollars in committed backlogs. Hyperscalers invest in AI startups and AI startups spend that money on the infrastructure of those same hyperscalers. Anthropic can’t afford it… and yet they do it. Estimates suggest that Anthropic’s server costs could reach 20 billion dollars only in 2026. The company is not yet profitable, but demand for its model family Claude continues to grow strongly in the business segment, which forces it to secure long-term computing capacity before infrastructure shortages prevent it from doing so. The agreement with Google adds to another recent one with CoreWeave and the forecast of securing almost a gigawatt of additional capacity through Amazon chips before the end of the year. Almost symbiotic relationship. Alphabet is at a time of maximum competitive pressure in AI. Your cloud business grew by 36% last year, and Anthropic is one of its most intensive clients. Losing that relationship, or seeing it migrate to other providers like AWS, would be a significant blow. Furthermore, with an Anthropic valuation that Bloomberg situates around 800,000 million dollars, and with a possible IPO Before the year is out, Google’s accumulated stake in the company could become one of its most valuable financial assets. It is not just infrastructure: it is also a capital bet. Cover image | Wikimedia and Fortune Brainstorm Tech In Xataka | If at some point NVIDIA has to choose between giving its best chips to the US or China, its choice is very clear.

Anthropic has just left behind Claude’s biggest burden. He has achieved this after sealing an alliance with Elon Musk’s SpaceX

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There are few things more frustrating than finding a tool that fits almost exactly what we need and discovering, just as we’re starting to get the most out of it, that we can’t keep using it at the same rate. Claude It has earned a prominent place among those who use artificial intelligence to program, analyze documents or work with demanding tasks, but it has also drawn a very specific complaint: its limits of use. We are not talking about a minor annoyance, but rather a friction capable of breaking the workflow. Anthropic has decided to attack the problem. The company led by Dario Amodei announced a rise of the limits of Claude Code and the Claude API, relying on a new alliance with SpaceXAI. The pact will give it access to Colossus 1, an infrastructure that Anthropic presents as a way to directly improve the experience of its most intensive users. The promise, for now, is clear: more room to use Claude without demand taking its toll so quickly. The tension with limits. The adjustment that helps understand this news came a few weeks earlier. Anthropic recently modified their time limits to better manage demand during peak hours. In practice, this meant that five-hour sessions could be consumed before those actual five hours had passed if the use occurred during peak periods. The change especially affected those who made more intense use of Claude. More room to use Claude. Anthropic specifies the improvement in three changes that, according to the company, take effect immediately. The first is the doubling of Claude Code’s five-hour limits for Pro, Max, Team, and Enterprise plans per seat. The second is the removal of the peak limit reduction for Claude Code on Pro and Max accounts. The third affects the API: Anthropic says it has considerably raised the usage limits for Claude Opus models, although the exact scope depends on the limits table published by the company itself. Colossus muscle 1. The agreement with SpaceXAI is the most striking piece of the announcement because Anthropic ensures that it will be able to use all the computing capacity of the Colossus 1 data center. According to the company, that means more than 300 megawatts of new capacity and more than 220,000 NVIDIA GPUs that will be available within a month. SpaceXAI also details that the cluster includes deployments of H100, H200 and GB200 accelerators. The transformation continues. SpaceXAI does not appear in this agreement as simply a new label within the SpaceX ecosystem. The context, Elon Musk noted that “xAI will be dissolved as an independent company” and that its artificial intelligence products will be integrated under SpaceXAI. The phrase helps understand why Anthropic is talking about this brand when explaining its new access to computing power. Of course, to avoid confusion, what Anthropic announced is not a purchase or a merger, but rather an agreement to use AI infrastructure. It is not an isolated agreement. Anthropic also wanted to frame the alliance with SpaceXAI within a much broader capability strategy. The company recalls an agreement of up to 5 GW with Amazon, which includes almost 1 GW of new capacity by the end of 2026, and another 5 GW pact with Google and Broadcom that will begin to come into operation in 2027. To this it adds a strategic alliance with Microsoft and NVIDIA, with $30 billion of capacity in Azure, and an investment of $50 billion in AI infrastructure in the United States with Fluidstack. The most futuristic part. The agreement also includes a much more speculative derivative. Anthropic says that as part of the pact, it has expressed interest in collaborating with SpaceXAI to develop several gigawatts of orbital computing capacity. SpaceXAI presents it as a possible answer to the pressure that AI is putting on energy, land and cooling on the ground, but for now we are far from something tangible. Of course, this route would only make sense if important engineering challenges are overcome first. The real challenge. Anthropic has put on the table a direct answer to one of the big complaints surrounding Claude, although the most important part is still missing: checking how it feels in real use. SpaceXAI’s new limits and additional capacity seem to point in the right direction for those who work intensively with these services. The improvement, therefore, opens a new phase: that of checking if Claude can offer more margin without its users encountering the same wall again too soon. Images | Xataka with Nano Banana In Xataka | The “token economy” is broken: flat AI programming fees are mathematically unsustainable

Anthropic and OpenAI know that where AI is making money is in companies. They have found a way to squeeze that strategy

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We end users no longer matter much to the AI ​​giants. These companies are confirming that income is currently in the professional world, and they are already making moves to conquer that segment. And if they have to do it company by company, so be it, because now OpenAI and Anthropic are a little less AI companies and a little more consulting. AI is more business than ever. Anthropic and OpenAI have understood that the real business of AI is not currently in individual $20 subscriptions, but in integrating their AI models into all types of corporations. Both companies have almost simultaneously launched alliances with other companies to provide consulting services. The objective is simple: to stop being external web tools to become the “operating system” of thousands of businesses through these exclusive sales channels. Anthropic on the one hand… The company led by Dario Amodei has formed a joint venture with Blackstone, Goldman Sachs and Hellman & Friedman valued at $1.5 billion. This new firm will act as a consultancy bringing Claude directly into the operating environments of mid-sized businesses, from mid-sized banks to local manufacturers to healthcare systems. These companies have committed to provide $300 million each for AI engineers to work closely with these clients to integrate custom solutions. …and OpenAI on the other. In turn, Sam Altman’s company has not been slow to replicate that initiative with the creation of the so-called The Development Company, an entity valued at about 10,000 million dollars. It is backed by funds such as TPG, Bain Capital and SoftBank. Theoretically, OpenAI has already raised $4 billion to accelerate the adoption of its AI models in more than 2,000 companies that are already part of those investors’ portfolios. The initiative is led by Brad Lightcap, until now COO of the company, and who wants to make the GPT family models an integral part of the operations of all types of companies. Engineers on the line of fire. To promote these strategies, both companies are adopting the so-called ‘Forward Deployed Engineer’ (FDE) model, a deployment system that was already popularized by Palantir and that consulting firms traditionally use. Instead of simply selling an API, Anthropic and OpenAI will send their engineers to work with doctors, financial analysts, or IT staff so that their AI models can be seamlessly integrated into those professionals’ real-world workflows. Going public as a goal. In recent months we seem to be experiencing a race against the clock towards the IPO in both cases. With absolutely stratospheric valuations (OpenAI 852 billionAnthropic hanging around 900,000 million), the pressure to justify these figures to the public market is immense. The integration of programming tools such as Claude Code has been a clear driver of recent growth, but the real gold mine is in the automation of processes in sectors such as health or finance. If you are joint ventures fail to scale quickly, the valuation bubble could deflate before those IPOs. Conflicts of interest. When a venture capital fund invests in a technology provider and simultaneously pressures its portfolio companies to adopt that same technology, competition ceases to exist. Many companies will not have much real choice based on product quality. What is reinforced here It is that “circular economy” in which innovation is not chosenbut is imposed by financial and business interests. The customer does not buy because he needs the tool, but because his own financial owner has a stake in whoever supplies that tool. But wouldn’t AI automate everything? The dependence on the FDE model is paradoxical. Theory tells us that software must be infinitely replicable at zero marginal cost. However, these alliances show that AI is still not smart enough to operate without direct human supervision. We need someone to teach us how to use it well, the companies say, and both OpenAI and Anthropic are going to take advantage of that need even if what we really have is luxury personalized consulting. For now, AI will be more part of the services offered by a consulting firm than a truly autonomous “plug and play” tool. New Job: Deployment Engineer. Now Anthropic and OpenAI will not only be AI companies: they will also be consultancies in need of manpower. That also serves as an example that although AI theoretically will eliminate jobswill also create new ones. Here we face a growing demand for “deployment engineers” —OpenAI already requests them—, professionals who are precisely in charge of adapting these AI models to the needs of companies that want to implement them in their daily lives. And the data, what. There is another fundamental problem: medium-sized companies will not have much capacity to manage their data sovereignty. For Claude or GPT to function properly in the business, they will need access to critical workflows, medical records, or sensitive financial data. And when one cedes that control to third parties, they remain vulnerable. Not only that: the security of this data is compromised because in order to process it, it must leave and be processed in the cloud of an external provider. The AI ​​models of these companies can also probably learn from these processes, although it is reasonable to think that Zero Data Retention policies will come into play (“No data retention”). Image | TechCrunch | Wikimedia Commons In Xataka | The White House wants to review new AI models before anyone uses them: first the Pentagon, then the rest of the world

Sam Altman attacked Anthropic for using fear tactics with their new AI. He then did exactly the same thing.

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The big AI companies have set themselves a goal: practically every week They must present a new model or start warming up the atmosphere by commenting on what is to come. Delays are not tolerated because the speed at which everything happens is overwhelming, but those who continue to dominate the conversation in terms of the power of their models are OpenAI and Anthropic. And what had to happen has happened: if Anthropic has a new “dangerous” model, now OpenAI says they also have one. And it is a example very clear of “where I said I say, I say Diego.” GPT-5.5 Cyber. A few days ago, OpenAI released GPT-5.5 Cyber. This is a variant of GPT-5.5 focused and specialized in advanced cybersecurity capabilities. It is a model focused on tasks such as the exploitation of vulnerabilities, penetration tests, malware reverse engineering and other types of actions highly focused on that sector of computer security. In a reality in which, thanks to AI tools, there are systems that are more vulnerable than ever (and all this when we are on the threshold of the era of post-quantum cryptography), such specialized models seem like a very sweet tool for companies. But, of course, also for someone with other intentions. Access control. Due to concerns over potential dual use, OpenAI has made the decision to restrict access to GPT-5.5 Cyber ​​to “critical cyber defenders.” Who are these? Those that protect essential infrastructure such as electrical or financial networks. OpenAI has a certified access program with robust safeguards and rejection of malicious requests so that not everyone has access to this tool. In addition, they have a monitoring system to detect suspicious activity carried out by the model. With cannon shots. It is, in essence, the discourse of fear. Once again, an artificial intelligence company saying that they have a product so powerful that it cannot fall into the hands of just anyone. It’s not the first time that OpenAI uses this speech, but the times have been very curious. A few days ago, Anthropic presented Mythos. It is a tool very similar to that of OpenAI, one that is already giving some results in companies, with examples like Mozilla pointing out that, thanks to Mythos, the latest version of Firefox has a lot of security patches because AI has greatly streamlined the processes for finding vulnerabilities. It is one more example of the two titans of the AI ​​industry captaining ships with enormous firepower and “shooting” their best product with that speech of fear. Precisely, that’s where the problem lies. The hypocrisy. After the presentation of Cyber, Sam Altman commented at X that they were working with the Government to establish trusted access control to their tool. They have not shared the identities of those who will have initial access or, really, many details of the model. It has simply been a “oops, oops, this is very powerful and we can’t release it to the general public.” And, as we say, the problem is that Sam Altman himself harshly criticized Anthropic’s strategy when Mythos was presented. The CEO spoke about the strategy of fear and compared the maneuver of Anthropic and its declared enemy, Dario Amodei, with that of someone who manufactures an atomic bomb and, at the same time, sells you the bunker to protect you from it. This has not been overlooked by the media because he harshly criticized that strategy just before copying it word for word. At par. Despite everything, neither one nor the other is wrong. When AI companies present a model, curiously it is always better than the competition in almost everything. On this occasion, a assessment The UK AI Security Institute reflects that both Mythos and GPT-5.5 Cyber ​​are two of the most powerful models they have analyzed in their cybersecurity tests and that they are, basically, on par. Compared to previous or non-specific models, the difference is palpable. In expert-level tasks, GPT-5.5 achieved an average success rate of 71.4% compared to 52.4% for GPT-5.4. Mythos Preview, for its part, stayed at 68.6% compared to 48.6% for Opus 4.7. The Institute concludes by pointing out that this is evidence that the potential in cybersecurity is a trend among frontier models, one in which they can begin to achieve the desired benefits in order to become listed companies. Another reading is that countries that want to stop depending on cutting-edge American technology must start getting their act together as soon as possible. And that is, precisely, the message from the CEO of Mistral, the French AI company that recently pointed out that Europe had to stop being a technological vassal of the United States to become a power. In Xataka | Someone has had a simple idea so that data centers do not collapse in Spain: “unplug them” 18 days a year

Anthropic is one step away from being worth as much as Samsung. And what the market is buying is not Claude

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Anthropic, the company behind Claude, is exploring a new round of financing that would value it at more than 900,000 million dollars. If it closes, it would surpass OpenAI as the world’s most valuable AI startup. Altman’s company set its needle at 862 million last month. The figure more than doubles the 350,000 million it had in February. In just two months. Why is it important. The valuation no longer reflects Anthropic’s sales. It responds to a bet on what the company can become in five years or a decade: a provider of something resembling an essential service. Anthropic bills Claude for subscriptions and accesses to its API. That business exists, grows quickly and has reasonable margins. But it does not by itself justify a valuation that is close to that of Samsung, the Korean megalodon that manufactures everything from the chips we carry in our pockets to the ships that cross the ocean. The context. What the market is buying with Anthropic, and as often happens in the stock market, is not the present, but a hypothesis: that a very small handful of laboratories will control the foundational layer on which the software of the next decade will be built. And that Anthropic will be one of those few. And it will do so in a very profitable way. The logic, on the other hand, is the same that led to overvaluing telecos during the bubble dotcom or to the electric companies at the beginning of electrification. Whoever owns the basic infrastructure sets the rules. Google has already committed 10 billion to the previous valuation, with another 30 billion conditional on objectives. Amazon has put in 5 billion and plans to inject 20,000 more. An IPO could come before the end of the year, around October. Between the lines. That Google and Amazon, two of the largest cloud companies in the world along with Microsoft, finance a company that also sells through them says a lot about how they understand the moment. They are ensuring supply, it is not just an investment in a supplier. It is the difference between buying shares in an oil company and buying a field. Anthropic is, for these hyperscalersa deposit. Yes, but. The hypothesis has its cracks. The models are commoditizing faster than it seemed a year ago. The technical difference between Claude, ChatGPT and Gemini It is measured in nuances, not in generational leaps. If foundational AI ends up being a commodity (something like electricity or water coming out of the tap), current valuations are unsustainable. If it ends up being an infrastructure with network effects and high barriers to entry (something like an operating system), they may even fall short. The market is paying for the second hypothesis. Time will tell. The money trail. Anthropic recently announced, with restrained fanfare, Mythosa model capable of detecting and exploiting vulnerabilities in critical software. The company deemed it “too dangerous” to release and has only given it to a closed group of companies for internal testing. Even so, it has been accessed by unauthorized users. That is exactly the reason why some investors pay these figures: such a model is not sold but granted. And whoever decides to whom it is granted has regulatory power de facto that not even a Samsung, at least outside of South Korea, has ever had. The big question. What happens if the bet goes wrong? A valuation of 900 billion means that Anthropic has to generate, at some reasonable point, revenues in the order of tens of billions a year with very high margins. It is possible. But it was also important for Cisco to maintain its 2000 valuation, and it has needed 26 years to tie. The difference is that this time the buyers of the bet are the companies themselves that depend on the result. This reduces the risk of a sharp correction. And he postpones it. In Xataka | There is a thing called “Ornn price index”, it is out of control and it is bad news for everyone Featured image | Xataka

We already know what happens to the GPU hourly price when OpenAI or Anthropic launch a new model: it doubles

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This week, an analyst named Tomasz Tunguz published in X two revealing graphs. They show the evolution of what it costs AI startups to access cloud computing, and there is bad news. The cost of renting the NVIDIA B200 GPUs with Blackwell architecture has gone from $2.31 per hour in early March to $4.95 per hour this week. It is an increase of 114% in just six weeks and it has a clear cause: the arrival of new models from Anthropic and OpenAI. What the graphs show clearly. Those charts focus on the price index of Ornna cloud computing trading marketplace. The first of them covers the price of renting the B200 chips from the end of 2025 until today, and there are vertical lines showing each release of the latest models from OpenAI and Anthropic. The correlation is almost perfect: GPT-5 Codex, Claude 4.5, GPT-5.3 Codex, Claude Opus 4.7 and GPT-5.5 coincide with a jump in price indices. Every time these companies announce a new version of their frontier models, demand skyrockets, and so does the cost. If you want the best, pay (much more). The second graph shows the price difference between renting the previous generation of chips, H200 with Hopper architecture, and the new B200. The historical average of that “spread” is $1.06, but now it stands at $2.09, practically double. That means buyers—startups and AI companies—are paying a record premium for the extra memory and superior computing power of Blackwell architecture chips. Accessing the latest of the latest was already expensive. Now it is even more so. This also makes the H200 in a second class option for the most demanding models of 2026. Action and reaction. There is overwhelming logic here. When OpenAI or Anthropic release a new model, there is an explosion in inference. Developers and companies want to test them as soon as possible and integrate these models into their products (or compete with them). To do this, they need computing quickly, and a simultaneous demand is caused that unbalances the available inventory in the market for renting AI chips by the hour. The problem is that the supply of B200 does not grow at the same rate. Some companies have wanted to anticipate, and we have the perfect example in Google. He has bought all the B200s he can, and that has made these GPUs around now the 500,000 dollars on the secondary market according to analyst Jack Minor. The irony of efficiency. The curious thing is that the more efficient these chips are – and the B200s are – the more companies want to rent them at the same time to take advantage of those efficiency advantages that should lead to cost savings. What actually happens is that the scarcity of these advanced chips cancels out any theoretical savings. Long term contracts. Startups and companies that think in the short term are especially harmed in this area, because they face price jumps that are increasingly difficult to assume. Companies that signed computer rental contracts at the price then can now operate at less than half the cost of their competitors. Thinking in the medium or long term seems reasonable, although once again those who win are the hyperscalers and those companies that have managed to get hold of many B200s. And who wins even more is of course NVIDIA, which cannot cope. Few alternatives. In other markets such as energy or metals there is usually room for maneuver, Tunguz points out, but the same is not happening at the moment in the AI ​​segment. In the oil market, for example, if the price rises 114% in six weeks, companies can buy futures, options or fixed-price supply contracts to protect their margins. In cloud computing rental, those options are much more limited. And the result is a much more volatile segment. This will go further. We are probably facing a peak in demand that will be followed by a correction: the new batch of B200 chips that arrive in the second half of 2026 are expected to cause a drop in current prices. However, that $4.95 is now the new floor, not a peak, because demand for AI computing will continue to grow faster than TSMC’s production capacity. In the absence of the supply of AI chips growing significantly – and there are certainly movements that are trying to achieve this, such as those of Google with its TPUsAmazon with its Trainium or Huawei with its Ascend—, the problem will still be there. In Xataka | Europe is taking its technological independence so seriously that it is aiming for the most ambitious goal: NVIDIA

chatbot is not working and Anthropic says it is investigating an issue

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This afternoon may not be the best time to leave any task in the hands of Anthropic’s AI. Most of the services of the company led by Dario Amodei are giving global failures this Tuesday. Everything points to a general decline, with two clear exceptions: Claude for Government and Claude Console, the management platform aimed at developers and companies. The details are visible on the Anthropic status page. claude.aithe gateway to the chatbot both in its web version and in the desktop and mobile apps, is completely out of service. We have been able to verify it: when trying to use it, the macOS application displays a clear message, “You cannot connect to Claude,” and invites you to check the Internet connection. They are also registering API problemsthe path that allows professional clients, such as developers and companies, to integrate Anthropic services into their own applications. This is the case of those who use it to power customer service chatbots or to access models such as Sonnet 4.6 and Opus 4.7 in Perplexity. On this front, the drop is partial: everything points to higher error rates or intermittent failures for some users. Claude Code It is also not spared and is experiencing a partial decline. The impact can be significant: it is one of the most established agentic AI tools on the market. Its adoption in developer workflows is increasing, so any failure can have direct consequences on the productivity of many people. For now It is not clear what caused the incidentalthough we do know that Anthropic teams are working to resolve it. The company itself has been updating the situation on its status page, which allows us to reconstruct a brief chronology of the events. April 28, 2026, 17:41 UTC (19:41 Spanish peninsular time). Anthropic detects the problem and begins the investigation. April 28, 2026, 17:51 UTC (19:51 Spanish peninsular time). Confirms bugs in the API, claude.ai and the login system. April 28, 2026, 18:33 UTC (20:33 Spanish peninsular time). It indicates that it is continuing to work to resolve the incident. For now, we just have to wait for the incident to be resolved. Claude chatbot users can use alternatives as ChatGPT, Gemini or Grok. The problem is evident: when the Anthropic service does not work, access is lost to key elements such as conversation history, projects and other associated data. We will update this article as soon as there is news. Images | Screenshot In Xataka | Kimi Code is eight times cheaper than Claude Code and does 75% of your work. The question is whether it is enough

Google will invest up to $40 billion in Anthropic because the new normal for AI is investing in your enemy

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May the rhythm not stop. Amazon announced an investment of 25,000 million in Anthropic a week ago, and four days later Google went even further. The Mountain View Company spoke on Friday of an investment of up to $40 billion in that same company. We insist: this is non-stop. The money doesn’t stop flowing. In less than a week, two of the largest “cloud providers” in the world have committed to investing up to $65 billion in a company that, attention, is a direct competitor in the AI ​​segment. None have done it out of generosity, and here there is a lot of covering one’s back and, of course, circular financing. This is the Google agreement. Google will invest $10 billion now considering that Anthropic’s valuation is between $350 billion and $380 billion. From there, it can invest another $30 billion linked to company performance milestones that have not been detailed. What Google gains. In exchange for that investment, Google Cloud will provide an additional 5 GW of computing capacity from 2027, expanding the agreement that Anthropic had already announced with Google and Broadcom to contract 3.5 GW of computing in the form of access to their TPUs. Google already invested 300 million dollars in Anthropic in 2023, but months later he put it on the table another 2,000 million more and in 2025 another 1,000. Anthropic is already worth a fortune. It is estimated that before this agreement its participation in Anthropic was around 14%, and with this new agreement that participation will evidently increase. Anthropic’s valuation has grown dramatically in recent months, and according to Bloomberg There are offers for a new investment round that would place its value at 800,000 million dollars, already at the level of the 850,000 million valuation that OpenAI is around. Its growth is overwhelming, and it is clear that today She is the pretty girl of the industry. No one could wait. The speed with which these announcements have occurred is motivated in part by the competitive fear between Amazon and Google. Anthropic uses Trainium chips from Amazon and TPUs from Google: it needs both and they both know it. Every dollar those companies put into Anthropic is a business case for Claude’s clients to use AWS or Google Cloud, so it makes sense that both want to solidify that “preferential relationship” with the company that is conquering the enterprise market. The circular financing model as a standard. This week’s agreements consolidate what many already consider as the new normal sector: hyperscalers invest in AI startups, and AI startups spend that money on the infrastructure of those hyperscalers. For example: Google Cloud grew 36% in revenue last year to $58.7 billion and Anthropic was most likely one of its heavy clients. The money Google invests in Anthropic comes back in the form of invoices, and the same goes for Amazon and Trainium. But the investment has another reason. These investment agreements not only seek to strengthen ties with the most promising AI startup of the moment, but also have a significant stake in its shareholders. That’s even more striking, because both OpenAI and Anthropic They hope to go public before the end of the year and if so, Google and Amazon will have “bought cheap” their stake in a startup that is expected to skyrocket exceptionally once it becomes a public company. Once again, this is a bet for the future. But there is also the other big reason: the majority of investors (be they funds or companies) do not want to be left behind in this race and are betting because everyone else is doing it too. It doesn’t matter that AI companies are losing money non-stop: the promise is that there will come a time (2029 or 2030) in which the trend will change. It is not certain that this will happen, of course, but OpenAI or Anthropic play with that card and use it to their advantage. We have the last example in Mythos, an Anthropic model that it’s so good (or so they say and some others) who prefer not to make it public. It’s once again selling expectations… and it works. In Xataka | DeepSeek has just released a model that competes with Opus 4.6. It costs seven times less and runs on Chinese chips

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