Bean bag charging is just the appetizer, B-end is the main course of AI commercialization, Titanium Technology presses the accelerator button for Agent marketing.

Since the beginning of this year, a clearer differentiation path has been emerging in the application layer of AI: on one end, there are consumer-facing C-end products, responsible for the tasks of the education market, capturing users, and cultivating user habits; on the other end, there are enterprise-facing B-end services, starting to take on more direct commercial goals and gradually becoming a key position for industry profit realization. On June 24th, Dou Bao launched its professional version and announced pricing, which many market observers see as an important step towards the commercialization of AI applications in China, and once again brings an old question to the forefront: as the user base of AI products grows and token calls increase, how should commercialization be implemented? From a larger industry perspective, the answer to this question may not only lie in C-end charging itself, but more likely in the gradually clear B-end opportunities after the differentiation of AI applications. C-end competes for entry, B-end competes for profits. In recent times, leading AI products have been continuously expanding their user base. According to Tan Daipi, president of Huoshan Engine, as of June this year, Dou Bao's large model daily average token call volume had exceeded 18 trillion, more than 10 times the growth of the previous year. For any large model platform, when call volume reaches this level, commercialization is no longer a question of whether to do it or not, but a question of how to establish a sustainable revenue structure as soon as possible. In this sense, the pricing of Dou Bao's professional version is essentially finding a balance between the huge user base and the high model costs. However, it primarily addresses the issue of payment for a part of the high-frequency C-end users, not the entire answer to ByteAI's commercialization. Because compared to the C-end which relies more on subscriptions, ads, and ecosystem conversion, the business logic of B-end AI is much more direct. Enterprises procure AI services in essence to improve business operations: reduce costs, increase efficiency, optimize processes, improve decision quality, or directly bring growth. As long as this kind of value can be verified and quantified, enterprises are more likely to form a stable willingness to pay. This revenue model does not rely on secondary monetization of traffic, nor does it rely on a long recovery after a huge scale of free users, but is built on a more direct business loop. This is also why, on the day before the pricing of Dou Bao's professional version was announced, Huoshan Engine synchronously released the Dou Bao Large Model 2.1 series and repeatedly emphasized its focus on intelligent entity development and enterprise-level mission delivery. It's not a question of which path is more advanced, but rather their different roles in the industry chain. C-end products are more like an entry point, addressing user scale first; while B-end services are more like profit centers, with the core test being whether enterprises are willing to continue paying for the real value brought by AI.