Cai Niao Launches New Unmanned Vehicle at Bicycle Price, Industry Faces Price War

Cai Niao has launched a new unmanned vehicle available for pre-order at a price of 16,800 yuan after discounts, which is comparable to the price of a bicycle. Meanwhile, Jiushi Intelligent has set the base price of its L4 level unmanned vehicle E6 at 19,800 yuan, shaking the entire industry. On one side, leading companies are achieving record financing amounts—Jiushi Intelligent leads with 3 billion yuan, while New Stone Technology and Haomo Zhixing have each surpassed 1 billion yuan; on the other, end product prices are continuously dropping at an alarming rate, nearly halving in some cases. This once-promising sector is now questioning whether unmanned delivery is a 'money-losing venture' or a 'new profitable track.' Amidst the noise and skepticism, can anyone really make a profit? With costs prioritized before scaling, what is the backing for this? The price war in unmanned delivery did not arise out of nowhere; it is based on a drastic drop in hardware costs. For instance, concerning the key technology of unmanned vehicles—LiDAR, the price trajectory of ADAS radar from Su Teng Ju Chuang is a microcosm of the industry. In 2025, CEO Qiu Chunchao announced that they would begin mass production at a cost of under $200 (approximately 1,447 yuan) and aim to lock in prices around 1,000 yuan. The dramatic drop in sensor costs has emboldened unmanned delivery companies to announce base vehicle prices below 20,000 yuan. Continuous capital injection provides long-term support for this price war. Jiushi Intelligent leads with a total financing of 3 billion yuan, and its diverse financing structure enhances its anti-cyclic ability, enabling a 'low-price vehicle' strategy. New Stone Technology has leveraged 2 billion yuan in financing to partner with logistics giants like SF Express and JD.com, spreading costs through large-scale orders. Even smaller finance-scale companies like White Rhino can maintain price competitiveness relying on SF's scenario resources. This cycle of 'financing-price reduction-expansion-re-financing' pushes the industry into an early stage of 'exchanging price for volume.' The entry of logistics giants into the market further intensifies price competition. Cai Niao's L4 unmanned vehicle is now priced at 16,800 yuan after discounts, entering the market at a 'bicycle price.' JD Logistics has developed an unmanned light truck, VAN, which integrates the entire chain to reduce the total cost of ownership (TCO) per vehicle by 30%. It is evident that both logistics and technology companies are making significant moves in cost control, and the price war has become a necessary choice to capture market share. Under the scale dilemma: from 'selling cars' to 'services,' companies are dumping vehicles at prices close to or below cost to capture scene entry points and operational data. While Jiushi Intelligent appears to be 'selling cars at a loss,' its core profit model is aimed at subsequent continuous fully autonomous driving subscription services—charging 1,800 yuan per month, resulting in a total service cost of 127,800 yuan over five years, far exceeding the vehicle price itself. Similarly, Cai Niao’s 'bicycle price' is fundamentally a strategic positioning that leverages Alibaba's ecosystem, deeply binding commercial flow and logistics scenarios. Specific cases show that the more fixed the scenario (such as parks or communities) and the denser the volume, the shorter the profit cycle. For instance, in urban delivery scenarios, Jiushi Intelligent can achieve an average of 120 orders per day per vehicle by binding with delivery points, nearing the break-even point; Meituan's unmanned vehicle, utilizing food delivery scheduling algorithms, has completed 5 million deliveries, reducing the cost per kilometer to 1.2 yuan, below the 2.5 yuan of human delivery. Although there are still scale dilemmas for unmanned delivery vehicles, their advantages as replacements are significant. For example, assuming a delivery person earns 6,000 yuan a month, the total cost over five years (including tricycle depreciation) reaches 360,000 yuan; meanwhile, the total cost of Jiushi's E6 over five years (vehicle price + service fee) is only 127,800 yuan, a cost reduction exceeding 64%. Even if the threshold of '80 kilometers and 120 orders per day' is difficult for individual operators to meet, JD, SF, and others with over 200 daily orders can easily achieve this. It is now foreseeable that the future profit models for unmanned delivery vehicles will be diverse: Jiushi's 'vehicle + service' subscription model, SF's open unmanned delivery platform, and JD's comprehensive approach of 'self-research + investment + scenario' all represent different paths of exploration. The key lies in whether companies can find a differentiated ecological niche that aligns with their resource endowments, building a sustainable profit pool. Conclusion: 'No scale, only price war' is the market's demand. In this context, capital reserves become the core criterion for distinguishing company tiers. While broadening financing channels is certainly important, there is a need to be wary of the myth that 'technology is omnipotent.' Companies must delve into segmented scenarios to understand real pain points—whether solving the 'last 500 meters' in closed parks or breaking through 'trunk breakpoints' in mountainous areas. Is the goal to optimize delivery timeliness for fresh goods or reduce labor costs for night shifts? Precise scene definition and the ability to meet demands are prerequisites for a commercial loop and the key to breaking the price war and achieving profitability.