Core Viewpoint - Li Auto's self-developed autonomous driving chip M100 has successfully passed key pre-mass production stages and is expected to be mass-produced next year, aiming to enhance efficiency and cost-effectiveness in its autonomous driving algorithms [4][6]. Summary by Sections Chip Development - Li Auto's M100 chip has completed functional and performance testing, demonstrating significant computational capabilities, such as matching the effective computing power of 2 NVIDIA Thor-U chips for large language model tasks and 3 Thor-U chips for traditional visual tasks [4][6]. - The company has allocated a budget of several billion dollars for the development of its self-research chip project, indicating the high costs associated with chip development [6]. Strategic Approach - Li Auto is adopting a dual strategy: relying on external partners like NVIDIA and Horizon for current market competitiveness while developing its own chip for future core advantages [7][8]. - The CTO of Li Auto, Xie Yan, is leading a strategy that combines hardware and software development to maximize chip performance and efficiency [6]. Market Positioning - In its current electric vehicle lineup, Li Auto is using NVIDIA's high-performance chips in flagship models, while employing a mixed strategy in its range-extended models by using either NVIDIA Thor-U or Horizon Journey 6M chips based on different autonomous driving versions [8]. - The core reason for developing its own chip is to optimize performance specifically for Li Auto's algorithms, enhancing cost-effectiveness and efficiency [8].

Core Viewpoint - Li Auto's self-developed autonomous driving chip M100 has successfully passed key pre-mass production stages and is expected to be mass-produced next year, enhancing the company's competitive edge in the autonomous driving market [3][5]. Group 1: Chip Development and Performance - The M100 chip has demonstrated specific performance characteristics, providing effective computing power comparable to 2 NVIDIA Thor-U chips for large language model tasks and equivalent to 3 Thor-U chips for traditional visual tasks like image recognition [3][5]. - Li Auto has allocated a budget of several billion dollars for the development of its self-research chip project, indicating the significant investment required for such technology [5]. Group 2: Strategic Partnerships and Current Solutions - Until the M100 chip is mass-produced, Li Auto will continue to rely on existing partnerships with NVIDIA and Horizon Robotics for its current chip solutions [5][7]. - The company employs a mixed strategy for its range-extended models, using either NVIDIA Thor-U or Horizon's Journey 6M chips based on the specific version of its AD Max and AD Pro autonomous driving systems [7]. Group 3: R&D Strategy and Challenges - Li Auto's CTO, Xie Yan, is driving a strategy that combines hardware and software development to maximize chip performance and efficiency, aiming to outperform competitors [5][6]. - The integration of hardware and software in chip development is complex, requiring deep technical expertise and effective collaboration across departments [6].