How is this possible? The approach that he took was to start to think about where the architecture was going to go. We define the architecture to be mixed critical from the get go. We decided about three years ago that the rate at which AI is expanding, it would be unnatural to separate the infotainment system from the ADAS system. These are, at the end of the day, taking into the vehicle sensors that the car is seeing, consuming it through AI. Yesterday it was computer vision, it was classical AI. Today it is called VLA, tomorrow will be called something else. But it really is the car being able to detect its environment through the lens of AI and then feeding it to various consumers, whether the consumer is the AI system, whether the consumer is the cockpit, or some combination thereof. Now, because the car is a safety product, it is designed inherently to be safe. We have to be able to think about this with a safety envelope all the time. We decided three years ago that we are going to over-dimension the silicon. We're going to build the most capable SoC that the industry has seen. We're going to do this on the cockpit framework, we're going to do this on the ADAS framework, and for customers that wish to do this together, they will have the flexibility, which is what we call Flex, to be able to go do this on the same exact platform. And you can see the multipliers, you can see how much we have grown the capability across really heavy dimension across displays, across CPU cores, across GPUs, across the NPU, across the number of sensors we can support. And this over-dimensioning is something that we converted into a chip that we supplied to the China ecosystem for the first time in January of '25. Here sitting in June '26, we see cars on the road. So first of all, a big thank you to the China ecosystem for embracing this capability and putting this on the road.
Now if I bring together everything that I've said so far, the Flex architecture gives you the best of both worlds. It allows you to be able to take cockpit capabilities and ADAS capabilities and run them concurrently. It allows the work, more importantly the software work, the hardware work, the testing, the ability to be able to build a model that is running on our silicon, make it binary compatible, allow it to be moved from one silicon to the next silicon, fundamentally accelerate the rate at which technology is moving, your software is being developed, and bring in a tremendous amount of flexibility so that you can reduce your overall system cost, so that you can take development that you did in a previous generation and carry it over to the next generation, really independent of any domain. The architecture is mixed critical, it is flexible, and it allows cockpit and ADAS to coexist. This also allows you to be able to very quickly move towards an agile world, because now on the same underlying platform you have access to every ADAS sensor, every cockpit surface area, every microphone, every display, everything inside the cabin and outside the cabin. So to be able to run an agile framework on top of such a platform makes it very straightforward.
We've been very fortunate to work with some of the best companies in China, and I'll show you here an example of DeepRoute running their stack on a Leapmotor vehicle on the 8797. This is commercial today. I want you to pay attention to this because this project was executed within about six months of the customer receiving the platform. This required very close coordination between Leapmotor, our OEM partner, DeepRoute, our stack partner, integrating it onto a brand new platform and deploying it commercially. This platform is now deployed on the road. The reason this thought process is so important is the rate at which the innovation is happening is independent in every area. Companies that are evolving their stack are moving very quickly. Companies that want to be able to go move to a hardware architecture are moving independently very quickly. The ability for us to be able to mix and match a partner who's working on a stack versus an OEM who selected a new car architecture and get them to start to work together to go deploy something, and within months make this happen, is testament to the capability, the flexibility, the versatility of the China ecosystem. It also has a lot to do with the way that the car architecture is evolved and how silicon and software architecture is evolving.
We are very excited to say that in China last year we accomplished our first 8775 Flex launch with BAIC. This was a result of tremendous work that was done by our partner Autolink and our partner ZYT, who we've been working with again independently for a number of years. But this came together in this partnership where BAIC decided to deploy the 8775, one of our first engagements with BAIC, and of course with Autolink and ZYT, who've been our partners for a long time. We've had nine different Flex wins, and we expect to see, as we deploy Gen 5 over the next couple of years, a lot of Flex deployments to start to take off in China. I would now like to invite Vice General Manager of BAIC, Mr. Liu Yu, who's been a new partner of ours, and we really welcome BAIC to the Qualcomm family. Welcome Liu Yu, Deputy General Manager of BAIC Group. Liu Yu.
Colleagues and partners, I'm very honored to attend this annual meeting of Qualcomm. I should say, as an automobile enterprise and a world-leading semiconductor company, it is a trend for us to have many projects. It is a trend towards the future. So what I want to introduce to you today is actually about chips. As I mentioned earlier, there is a Flex architecture 8775 chip. As for BAIC Group, last year we mass-produced the world's first solution based on the Flex architecture, integrated cockpit and ADAS solution. We are on the Jihu Alpha T5. Here, I want to share with you, we tried the world's first solution with this. Our entire development process. Let's turn the clock back to the fourth quarter of 2024. In fact, the problem we faced at that time was that high-level assisted driving had been mass-produced. Most of the models equipped with it were all above 300,000 RMB. So we understand that assisted driving, especially high-level assisted driving, the urban NOA we often talk about, should be standard equipment. Whether it's a 500,000 yuan car, 300,000, 200,000, 100,000, or even cheaper cars, should be standard. In the history of automobile development, we have seen that the ABS and ESP that we thought were optional features are now standard. So based on this idea, we thought, for the price range of 100,000 to 200,000, especially with 120,000 as the entry price, to mid-range family cars of 200,000, and high-level assisted driving, this is a huge challenge for us. We know that good things are expensive. Hardware takes up a lot of cost: the cockpit and autonomous driving, two chips, two pre-controls, and two power supply systems. This is a huge challenge.
In the fourth quarter of 2024, we encountered another phenomenon at that time: from BEV to end-to-end, whether it's two-stage or one-stage, from rule-based and code-based to a model-based pricing scheme, to change again. At that time, we heard many industry experts or colleagues say we were considering whether to delete the code, whether to continue with rule-based or end-to-end. Meanwhile, in the automotive electronics industry, there has always been a theory to guide us forward, which is the evolution of electronic and electrical architecture. It should be based on central computing, and the combination of software and hardware. So in that environment, we held a technical seminar in the city of Wuxi, which strengthened our determination and confidence in continuous progress. So we can see that we should have set our goals and we should find solutions. So we started to look for, from chip pricing, pre-control to project management. We also did some work ourselves. BAIC, in terms of intelligence, we have done a department integration ourselves. We know that many car companies have the cockpit and intelligent driving as two teams, two independent R&D teams. We have always insisted on being one team. We have a director in charge. So on this basis, we believe that with the 8775 chip, to promote the cockpit-integrated solution. So we formed such a four-party development and cooperation team. BAIC is responsible for demand definition, project control, integration, and verification. Qualcomm provides the solution of the underlying chip. Chelian World, as a pre-control explorer, and strongly promote the project's implementation. We also collaborated with Zhuoyue and City NOA to make the model smaller and make the experience better, and jointly plan.
As you know, the NPU dense computing power of the 8775 chip is only 72 Tera. In the current high-level autonomous driving, this solution is required. How can 72 tera operations per second? This is also a huge challenge. So our four-party joint team launched the project on February 19th last year. On October 30th, the first mass-produced delivery of Jihu Alpha T5. It took us eight months. The whole process was very tangled and challenging. Many friends in the industry told us, don't touch this: two underlying architectures, two systems, and a large amount of data communication and handshake. Vehicle high-level assisted driving requires millisecond-level, but the cockpit doesn't need it. This is an impossible path. We thought that since we chose this route, we must make it work. So the four-party team has realized mass production. Now we not only have Arcfox Alpha T5 and Alpha S5, including the recently released Wendo V9, are all equipped with the 8775 solution. So we can see that we doubled our performance in Jihu last year. Our consumers' experience with this solution, especially the experience of urban NOA, is very pleasant. And we have also controlled it well. Especially in the face of chips and memory prices rising, we share a memory system. We also developed standards for enterprises and accumulated experience in standard processes.
So in the future, we still need to focus on chips. We believe that the next generation of VLA-based, trained on world models, high-level assisted driving will further require computing power. So the cockpit fusion route we think is a viable path. At the same time, this platform should be continuously upgraded. The increased capabilities should not only include but also AI capabilities. So let's imagine the new generation of cars. We think it should be at the end of this year, in 2027, we should be the standard of the new generation. In terms of assisted driving, the car understands you better. With you, the city, and the environment are smooth and fluent interaction. This uses language to guide driving. This should be no problem. At the same time, we should put a smarter brain in it. Maybe like Jarvis to Iron Man, and omnipotent to assist. So we also hope that this is an ecosystem, not just starting from today, from solutions to the definition and development of vehicles, including the user's usage environment, to form a definition and development and continuous iterative working environment, to provide consumers with more complete, more satisfactory and safer solutions. Thank you.
Thank you very much, Mr. Liu. His partnership with BAIC has been fantastic. I had a chance to ride in the vehicle myself a few months ago, and it was a fantastic experience. We're really delighted to have Flex already on the roads in China. I'd like to draw your attention to connectivity. We've been supplying connectivity into cars since the early 2000s, when CDMA entered into North America. Today we are starting to see satellite connectivity becoming a requirement in a number of different mission-critical commercial far-flung areas. And as the number of constellations with connectivity increase globally, we start to see this as yet another new level of innovation. We've been driving the connectivity block inside cars for a number of years, and we believe that this is actually going to be a really interesting way to have yet another modality, yet another link back to all these connected vehicles.
I would like to share with you a little bit about what we are seeing in the car in the context of AI across other use cases. The car is becoming this platform where there is so much content, so much data, so many insights to draw from everything that the product is capable of. Using AI inside the vehicle outside of use cases beyond driving, beyond the in-cabin experience that we talked about, these are use cases that are relevant for the car itself. Automakers are continuously interested in trying to figure out how to get early warning information so they can spend less on predictive maintenance, so that they can reduce their warranty costs. And we are starting to see, as part of the efforts that we are driving through Edge Impulse, which is a machine learning ops platform that we're deploying inside the vehicle, the ability to be able to collect data, whether it's time series data, machine learning data, run local models and extract insights, extract intelligence. We are still continuing to use the same NPUs that sit on our platforms, and this allows us to be able to add yet an additional layer of insight from a machine learning and AI perspective.
I would like to now welcome Jeff Zhang, Chairman of Banma Intelligence. Banma has been a fantastic partner of Qualcomm for many, many years, but especially now in the age of AI, as we start to think about how new models, advanced models like Qwen, how new use cases and experiences from e-commerce to bringing mobile experiences into the vehicle, doing it where you have cloud and edge working together, how does this all come together? I would love to have Jeff share his vision with us. Jeff Zhang. Let's welcome Alibaba Group partner, DAMO Academy's director, and the chairman of Banma Intelligent, Zhang Jianfeng. Welcome, Jeff Zhang.
I'm very happy to have this opportunity today to share with you what we are doing at Banma. You must be wondering why am I representing Banma to talk about this? Because in about 2014, Alibaba, at that time, we proposed a concept called Internet car. At that time, the Internet had reached its peak state, especially Alibaba's own e-commerce was also developing very well. And at that time, artificial intelligence represented by deep learning, this technology was just emerging. At that time, there was also a background: the OS, especially represented by mobile phones, various operating systems was also on the rise. So at that time, I had an idea: whether we could make cars become more interconnected and connect with a huge life platform like Alibaba. I remember very clearly, at that time, our first idea was we wanted to use maps as the core of an intelligent cockpit, and we spent a lot of effort and then we made our own OS system of Alibaba. Of course, at that time, I thought that various hardware and conditions were still very restricted. My cockpit was also like Qualcomm's, which was originally migrated from the mobile platform, unlike today. Today, I think the most important thing is that Qualcomm has launched a dedicated solution for smart cockpit and also has a dedicated solution. This is a huge progress in the industry. So since we launched this smart cockpit in 2015 to today, it has been about ten years. The industry has also undergone earth-shaking changes, but the technology has also undergone earth-shaking changes. Well, everyone knows that I am also an engineer. I also come from an engineer background. I code. In terms of software and systems, it has changed a lot. Whether it was the Internet or something else, it was actually data-centered and database-centered. We were just reading, processing, and writing back information. Everyone, essentially, we were doing the same thing. Most of the interactions were command-based. It was probably such a system. So in that era, it was very simple. Think about it. If there is such a pattern, who would be the best in this field? Right, like databases. It must be the database, right? Because all systems revolve around it. Today we are all talking about artificial intelligence, right? Artificial intelligence has undergone a great change. I think for the software industry, or future systems, will bring a fundamental change. Because the current entire system is not built around this database or something like that, or some other basic building blocks. It is built around an intelligence, the so-called AI. What is the most important ability of AI? Reasoning. So it is based on this reasoning ability are built. So I think in the future, all systems will be reorganized around reasoning. There is a reasoning here. It's more powerful than previous systems and your human ability. So all systems need to be restructured. I will take the part of my original system parts that require reasoning, I have to hand over to this so-called large language model. Right? So what did I do before? What I used to do, I need to do it at night, right? If I need to, and then complete the specific work. After completing the special work, how to do it better? Specialized work. Now there are many new words invented: skill, choreography, and crawl and so on. Just now, this brain hole and many previous sharing, they all raised a very good question. I have very good brain and I have very good technical facilities. So how can I build such a rich application at the top? This is what I think is the value such service providers should exist.
As we all know, the most important contribution of modern industrial civilization is division of labor. Everyone does what they are good at. But I know that there are many car manufacturers in China. They are vertically integrated and they may be very successful. But I think division of labor is not about sharing the cake, right? Division of labor definitely creates new value. We empower merchants, making the industry more prosperous and make the industry more innovative. This is what I think is our purpose. Although Alibaba also makes chips, and our DAMO Academy is also making chips now, but we don't make car chips. We think it is a very professional industry. So what do we want to do next? What do we think we should do? Let's look at the automotive intelligent cockpit in this field, including brackets, what changes have occurred? Because it is a car after all, right? I am in the loop. We can divide the system into people in the loop, and people are not in the loop. The system with people in the loop, it needs to perceive the world. So our car as a physical carrier, it will definitely have more and more perception abilities, including voice, including air conditioning temperature. Anyway, many of them have this perception ability. After having so many perception abilities, how can I make it more intelligent? I think the first step is to integrate all these perceptions, right? Second, I need to reason, right? And decide what to do. This is what a language model should do, what a language model might do. Third, I need to provide a service. How can I use the perception I have obtained as an intelligent reasoning, what kind of result I can get. All these things, I think we need a new system. The core purpose of this new system is to shield the complexity above. And for the application development above, to provide more valuable, cost-effective, innovative means to allow our customers to develop faster. As Liu from BAIC just mentioned, we might have taken eight months and it will take a long time, but now it may be shortened to three months, right? Because we can do a lot of work. From this perspective, we are thinking that what's the essential difference between cars? What is the essential difference? I think in the car, it is very, very important. It needs a very low latency and a very natural interaction. As I mentioned earlier, I think we haven't fully achieved it yet. We are working hard in all directions. You can't wake it up. You can't just say a word to him and wait for a while for a response. You can't always take the initiative to initiate everything. There are many similar things. So we call it active intelligence. This is DS. And my model is different from the Dayu model. The Dayu model, everyone knows, now the manufacturers that provide the model are all about depth and breadth. Because they need to complete long tasks and do long reasoning. Their current goal is to work continuously for 24 hours on one task and continuously finish it. But obviously, this is not the case. A car may be I provide services related to the purpose of travel, and the travel itself, including emotional value, including some destinations for travel, including entertainment and services. This is different from the optimization goal. So the goal we propose is we need to provide a very sophisticated model on the side. Its core is to serve the travel itself and the car itself, and provide extremely low latency and cost. This is the core. We have also launched our own, called Auto Command, this model.
And then, our next step, the fans I just mentioned, right? The cooperation between Alibaba and Banma, Banma's cooperation with various car manufacturers. Our core foundation, we still provide an AliOS, right? We hope to shield the complexity of the hardware to provide a very good operating system. Today, this operating system, Qualcomm is also talking about we need to integrate, right? We need to integrate computing power, and isolation in security, and intelligence, to support large models. Of course, there is also data privacy protection and so on. This is what we hope to provide: a basic OS and then provide a basic ability on it. On top of that, we hope to provide some of the native applications, including integrating services. There are many Internet services, right? There are also many entertainment services. We don't need every manufacturer to connect with us. We hope to integrate these standard and Internet application services. Thirdly, we hope that during this event, our partners can develop their own personalized and customized applications. This is what Banma hopes to do. We can achieve. Well, today, I think it is also very meaningful to have this. I'm very grateful for this opportunity to meet so many colleagues in the automotive industry. After listening to the previous sharing, I feel more confident, right? And Qualcomm, today, we provide a very good computing platform. Like Banma, provides a very good operating system and intelligent native and future-oriented operating system. Then we provide basic applications, and then together with our partners, to enrich the entire automotive application ecosystem and accelerate innovation. Thank you all.
