OpenAI opens LUNA for free, why is DeepSeek increasing its price?
Author: Shenzhao TechFlow
Original title: OpenAI Sinks Down, DeepSeek Moves Up
On August 7, OpenAI announced that ChatGPT has reached 1 billion weekly active users, while opening GPT-5.6 Luna to free users with unlimited text conversations.
The day before, several DeepSeek API users were notified:The company plans to raise the overall price of API services in the near future. “A significant increase is expected”. The specific price and execution time are awaiting subsequent announcements.
This seems a bit counterintuitive.
Over the past two years, the best storyline for big Chinese model makers was the ultimate price-performance ratio. DeepSeek previously offered performance close to GPT-4 at less than one-third of OpenAI's price. Known by the industry as the “price butcher”, Liang Wenfeng became “Liang Sheng”. Everyone's consensus was:The core advantage of the big domestic model is to put the cost of using AI to the floor.
Now that the floor is loose, OpenAI has become the one to give free stuff to the world, while Chinese manufacturers are starting to talk about payment and price increases. Did the position really change between offense and defense?
OpenAI: free is not charity
Make one thing clear: GPT-5.6 Luna isn't OpenAI's strongest model. It is positioned in a medium ability range and is more than adequate for handling everyday conversations, simple writing, and basic translation, but complex reasoning and multi-step code analysis still relies on the more advanced SOL series. OpenAI takes a “just enough” model to cover the widest range of user scenarios.
This strategy has both ambition and costs.
The motivation comes from the cost side. In the past 18 months, the unit token cost curve for big model inference was astonishingly steep: model architecture optimization, mature quantification technology, and inference engine upgrades were superimposed. The same computing power cluster can serve tens of times more requests today than two years ago. When the marginal cost is low enough, free is close to the logic of Google search: free entry, ecological payment.
The costs are just as clear. In the first quarter of 2026, OpenAI's revenue was $5.7 billion, and the non-GAAP operating loss rate was -122%. For every dollar earned, $1.22 was inverted, and a net loss of $14 billion is expected for the full year. In one billion weeks of activity, 50 million paid subscribers, and a payment rate of about 5%.
Subscription fees obviously can't support this company. The money comes from elsewhere: the advertising business went live for 6 weeks to $100 million in annual revenue; the corporate API continues to expand, Codex has 5 million weekly users, and enterprise customers currently contribute more than 40% of revenue...
In other words, ChatGPT's business model is shifting from “selling model subscriptions” to “collecting platform taxes”: the model itself is free, and advertising, corporate services, and the developer ecosystem built on top of the model are the sources of revenue.
One billion weeks of life is the core of this game. It doesn't require every user to pay; it only requires users to open it every day, and then charge from a small number of high-value demands. This is a very classical set of internet platform economics. Previously, it was often compared to Claude's “enterprise market, paid programming” route. Looking at it now, OpenAI is an ironclad entry point for the people in the AI era.
DeepSeek: The server can't hold up
DeepSeek's situation is completely different from OpenAI.
V4 Flash is at the top of OpenRouter's weekly global call volume list, processing 7.22 trillion tokens in a single week. According to OpenCode data, on August 1 alone, V4 Flash's daily processing capacity reached 8 trillion tokens. There were frequent interface overruns and stuttering during peak weekdays. The peak and valley pricing mechanism was first introduced in mid-July (peak doubling), and a sharp overall price increase was directly predicted on August 6.
Put another way:Too many users and insufficient computing power.
Too low pricing attracts a large number of low-frequency, low-paying requests, and server resources are being squeezed out by invalid requests. Instead, enterprises and developers that really need deep reasoning cannot get a stable experience.DeepSeek needs to keep users who use AI as toys out of the door and keep those willing to pay for high-quality inference.
Doubao launched the paid version on June 24 (68/200/500 yuan for three monthly fees, basic functions remain free). It is an action on the same logical line. It has 345 million monthly activities, consumes an average of tens of millions of yuan in deductive costs per day, and e-commerce commissions cannot be reimbursed.
Today, domestic big model competition is heating up, and the financing environment is getting colder. Lack of computing power has always been a tight curse. In the past, the style of playing by relying on capital to renew one's life and unlimited subsidies was unsustainable, and proving that you can make money has become a more urgent task than proving that you are ahead in technology.
Of course, the price increase for large domestic models does not mean abandoning the price advantage. More accurately, the cold start phase of the price war is over. The task at the previous stage was to “make users use it,” but now the task is to “make users willing to pay for good things.”
One sinks down, the other goes up
When GPT-4 was first released, everyone compared model abilities. Who read more books, and who got higher test scores. At the GPT-5.6 Luna stage, the gap between the top models has visibly narrowed, and the marginal benefits of continuing to measure benchmark scores are getting lower and lower. Competition is shifting from “who is smarter” to “who is more inseparable”.
OpenAI chose to promote free of charge on this node, betting on the length of time and entry position of the user. It wants to make itself the default way most people approach AI, just as Google used to be the default way to search.
When China's big model makers choose to raise prices or promote paid versions, they are looking for certainty in a closed loop of commerce under the double pressure of declining capital and computing power controls, and are no longer satisfied with the “many users but not making money.”It is necessary to prove that the big model business can make hematopoiesis independently.
In the opposite direction, anxiety is symmetrical.
OpenAI must prove that the platform tax can cover inference costs before the financing window closes; Chinese companies need to turn the size of users into sustainable income before computing power peaks.
This differentiation may eventually grow into a three-tier structure.
The bottom level is everyday conversation and general Q&A. Model power has overflowed, the cost is negligible, and free will become the norm.Whoever charges here will be abandoned by users. OpenAI made Luna free to bring as many people as possible into this tier.
The middle layer is professional reasoning. Code generation, data analysis, legal assistance, and medical diagnosis. These scenarios have rigid requirements for accuracy and depth, and users are also willing to pay for the results.The paid versions of DeepSeek and Bean Pack focus on this layer.
The top layer is Agent execution. AI is no longer just answering questions, but directly completing operations for users: talking about business, fixing codes, passing audits... At this level, the billing model will change from “billing per token” to “billing by results.”
Everyone has their worries and dreams.
OpenAI sinks down, gambling on entrances and habits, and wants 1 billion people to be inseparable from it; China's big model is moving up and wants users to actively pay... Both dreams are not cheap; only one thing is certain:The era of free regardless of cost is over, and the free ones left behind are all businesses that can be counted as paying bills.
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