The “Fast and Furious” of the edge AI model world has unfolded before our eyes.

At the Shanghai Auto Show, amidst the launch of new models by Changan Mazda, the vehicle’s smart cockpit emerged as one of the standout highlights.

Why? Because the speed was truly astonishing—going from zero to mass production in just 10 months!

In the automotive industry, such developments are typically measured in years.

This move stunned the industry, breaking records and shrinking the development timeline from “years” to mere “months.”

And who achieved this feat? A relative newcomer in the automotive sector—ModelBest.

Yes, that’s right—the edge AI player known for its “small beating big” strategy in the large model community.

Its flagship product, MiniCPM, has long led global innovations in edge AI performance and algorithms, firmly establishing itself as a top-tier edge model provider.

By leveraging models ranging from under 1B to 8B parameters, ModelBest achieved remarkable GPT-4V and GPT-4o-like results on the edge. Recently, it released the world’s first fully multimodal edge model.

Its stellar reputation stems from high efficiency, low cost, and its ability to achieve significant impact with smaller models. Since early this year, it has often been referred to as the “Edge DeepSeek.”

The smart cockpit product it unveiled is called cpmGO, the industry’s first intelligent assistant driven entirely by a pure edge large model.

Video Link: https://mp.weixin.qq.com/s/O7UfPfxD8mN41IKN2E6ywA

Overall, cpmGO features the following key characteristics:

• Fast, Accurate, and Stable
  • 91% ultra-high execution accuracy, ensuring smooth interactions.
• Purely Local
  • Data never leaves the vehicle; response times are as fast as milliseconds.
• All-Scenario Coverage
  • Unaffected by weak or lost network signals; remains rock-solid in tunnels and mountainous areas.

It possesses end-to-end perception, decision-making, and execution capabilities spanning from outside to inside the cabin. This includes not only the first pure edge, Always-On GUI Agent screen assistant deployed last December but also a native edge experience fully aligned with cloud services. The next generation will introduce fully multimodal pure edge cockpit products.

Behind this technology lies adaptation and optimization by over ten mainstream chip manufacturers, including Qualcomm, MediaTek, Intel, NVIDIA, Xingchi Technology, and Sinetron, among other domestic and international platforms.

Looking across the entire Shanghai Auto Show, although ModelBest did not have its own dedicated exhibition booth, its presence was felt everywhere.

ModelBest has already partnered with major automakers and Tier 1 suppliers such as Changan Mazda, SAIC Volkswagen, Great Wall Motor, ThunderSoft, Wutong Technology, Desay SV, Aptiv, and others.

Indeed, this is a true “Fast and Furious” story of large models in the automotive world.

How Did the “Fast and Furious” Edge Large Model Achieve This?

Before diving into the technical details of cpmGO, let’s first explore more of its product capabilities.

For instance, with cpmGO, you can control the screen directly via voice commands, such as opening the dashcam to take photos:

When obstacles appear ahead, the vehicle can automatically identify them and execute deceleration:

It proactively detects driver fatigue and, in advance, prepares World Cup videos for “football fan” owners to watch during short naps:

If you simply say:

I want to see the stars.

Then cpmGO, accompanying you on a coastal drive, will proactively break down this intent and provide detailed route and campsite planning—automatically finding campsites away from city lights, equipped with water, electricity, and WiFi:

If there are children in the car, cpmGO will recognize them, carefully monitor their safety, and engage in storytelling or witty interactions based on what they say:

Notably, all the above scenarios can be performed even in offline modes.

After seeing these capabilities, let’s examine how cpmGO was developed.

First, regarding its pure edge architecture:

cpmGO is powered by ModelBest’s self-developed MiniCPM edge large model. It runs entirely locally on vehicle infotainment systems and other terminal devices, without relying on cloud computing power.

This design avoids data uploading, ensuring privacy and security (e.g., sensitive in-car voice and image data never leave the vehicle).

By maximizing knowledge density, MiniCPM compresses large models into sizes suitable for edge deployment while maintaining alignment with cloud-based models (such as multimodal understanding and complex intent judgment). This achieves a balance between performance and power consumption, enabling millisecond-level response times on vehicle chips.

In scenarios with unstable networks, such as tunnels or mountainous areas, the pure edge model continues to provide full functionality, solving the network dependency issues associated with cloud-based solutions.

Secondly, in terms of multimodal perception and interaction:

cpmGO integrates multimodal data from vision (in-cabin cameras), voice (microphones), and graphical UI (central control screens) to enable “what you see is what you say” interactions. For example, users can operate screen content directly via voice commands without touching the screen. With an action execution accuracy exceeding 91%, it significantly enhances the human-vehicle interaction experience.

From perceiving external environments (e.g., obstacle recognition) to understanding internal intents (e.g., “lower the AC temperature”) and executing actions (automatically controlling the infotainment system), cpmGO forms a closed-loop intelligent service from end to end.

Additionally, the Screen Agent (GUI Agent) is another major highlight.

cpmGO incorporates the industry’s first pure edge GUI Agent, which can understand screen elements and execute operations (such as clicking or swiping).

Unlike traditional “Q&A-style” AI, cpmGO is designed as a proactive service agent capable of continuously executing long-term tasks based on context (e.g., itinerary planning, cabin environment adjustment).

For instance, if a user says, “Open navigation to go to the office,” the Agent automatically completes steps such as launching the application and entering the address.

Official data shows that its intent completion rate reaches 89%, action execution accuracy is 91%, and parameter recognition accuracy is 97%—approaching human operational levels.

The steadfast belief in models that are both applications and compact, high-performance “steel cannon” solutions serves as the core energy source behind all of CPMGO’s technical secrets.

On-device Large Models Enter Vehicles: Witnessing the True “Car Awakening Moment”

Speed comes not only from internal capabilities but also from deep ecosystem synergy and partner support! Only by achieving rapid deployment and precise layout within the supply chain ecosystem can we ensure that vehicles run fast, run steadily, and run far.

There are two more pieces of good news from the auto show:

• Wallbox Intelligence (Mianbi AI) has established a strategic partnership with Intel to jointly develop on-device native intelligent cockpits, defining next-generation in-vehicle AI;
• A strategic cooperation has been reached with ThunderSoft to create a new experience for next-generation smart cockpits.

Currently, large model technology is officially crossing the cloud barrier, awakening and evolving on the edge device side.

Mianbi AI and Intel have jointly released the first “In-Vehicle Large Model GUI Agent” and are engaging in complementary, deep cooperation with ThunderSoft on its AI-native vehicle operating system, “Droplet OS Platform.” This brings on-device AI large models into car cockpits, allowing users to enjoy convenient, intelligent cockpit experiences anytime and anywhere, without being restricted by network conditions.

On-edge models naturally possess advantages such as closer proximity to users for more responsive reactions, stronger data privacy and security, and better stability that breaks through network limitations. They understand user preferences better, are trustworthy in terms of safety, and inherently possess a stronger ability to “put themselves in the user’s shoes.” This makes them ideally suited to serve as the “First Brain” in edge-cloud collaboration, providing immediate responses and task distribution.

From the “Density Law” proposed by Mianbi AI & Tsinghua University team:

The knowledge density of large models doubles every 3.3 months; for the same model performance, parameters are halved every 100 days. Vehicle chips are rapidly converging toward Transformer architecture-based large models. Chip micro-architectures are being deeply optimized for general algorithms used in large models, while chip manufacturing processes and performance advance steadily, making inference speeds on vehicles increasingly faster.

We can observe that vehicle-side models and chips are collaborating, continuously innovating, and evolving in depth.

Focusing on “Pure On-device Intelligent Cockpits” is the inevitable path to laying out for the future and advancing automotive intelligence. Furthermore, only by deploying the “brain” at the terminal edge can we ultimately achieve AGI in the physical world.

Now, let us redefine the future using three technical coordinates:

• First, the golden ratio point of edge-cloud collaboration has arrived. Within cockpit domain controllers, we are now capable of hosting full-modal large models equivalent to GPT-4o levels; next-generation products will introduce fully modal pure on-device cockpit solutions.
• Second, a paradigm revolution in privacy and security is underway. On-edge large models are developing deeply into personal large models. The luxury of privacy and security constitutes the greatest luxury of automotive cockpits.
• Third, the awakening process of car robots has begun. On-edge large models are no longer mere functional modules but serve as the “digital brainstem” of the vehicle.

When on-edge large models complete synaptic connections with intelligent driving systems, we will witness the true “Car Awakening Moment.”

As automakers announce vigorous layouts in AI, on-device large model companies represented by Mianbi AI are accelerating efforts to build an edge-side intelligence ecosystem alongside key players in the ecosystem. This ensures that artificial intelligence is no longer an external device attached to a car but becomes an innate intelligent core, much like a “car robot.”

Where There Is a Road, There Is a Large Model

Let us look at several more sets of data:

The current smart automotive industry is trapped in the dilemma of “computing power involution” (excessive competition). In terms of cost, the price of a single flagship cockpit chip reaches $300–$500. Combined with annual cloud service fees, this increases the overall vehicle intelligence cost by 5%–8%, placing an increasingly heavy burden on the automotive industry.

In terms of user experience, network fluctuations lead to delayed voice assistant responses and navigation lagging. User surveys show that 87% of car owners have experienced the awkward scenario of “smart functions suddenly failing.” Cloud-based intelligence in vehicle scenarios naturally faces the risk of suddenly becoming “disoriented” when encountering weak or no-network environments.

When the “computing power arms race” reaches its end, efficiency ratios will become a new dimension of competition and the “second curve” for automotive intelligence.

The proposal of CPMGO effectively addresses these pain points through our aforementioned characteristics: “Pure On-device, Super Performance, Full Scenario.”

The inspiration drawn from CPMGO lies not only in the technology itself but also in pointing toward a more fundamental trend: True intelligence should be as ubiquitous as air yet never overshadow its purpose.

When computing hegemony is dismantled and data barriers are broken, we may finally touch upon the ultimate proposition of artificial intelligence—letting technology humbly serve humans, rather than forcing humans to adapt to technology.

From ENIAC filling an entire room to iPhones fitting into pockets, the essence of the information revolution has been the decentralization of power; and CPMGO’s representative edge-side intelligence is returning control of AI to every ordinary person in a similarly irreversible manner.

In addition, the boundary between roads (the physical world) and AI technology (the digital world) is becoming increasingly blurred. Perhaps in the near future, it will truly be possible to use AI without internet access—where there is a road, there is a large model.