D100 specifications and claims: Xiaomi says the chip has a 20-core high-performance CPU, 16-core NPU, and support for up to 160 GB of unified memory. It says this enables local execution of AI models with up to 200 billion parameters. 12

Process-node claim: Xiaomi calls D100 mainland China’s first high-compute smart-driving AI chip built on a 3 nm process. That is Xiaomi’s claim; the company did not disclose a TOPS figure, the foundry, a first vehicle model, or a precise vehicle-installation timetable beyond planned 2027 commercialization. Consequently, its raw inference performance cannot yet be compared credibly with rivals’ published TOPS ratings. 1012

AI Cube demonstration: Xiaomi also showed a 150 W AI Cube Prototype combining three Xring chips: the O3 mobile SoC, O100 AI accelerator, and D100 automotive processor. The demonstrated unit reportedly had 80 GB unified memory and ran a local “120B + 3B” model configuration; it was an engineering prototype, not a commercial product announcement. 5

Nio: Its 5 nm Shenji NX9031 is already deployed in Nio and Onvo vehicles, with more than 300,000 units shipped; Nio has previously claimed over 1,000 TOPS per chip. D100’s 3 nm node is nominally more advanced, but Xiaomi’s undisclosed TOPS, power, bandwidth, safety architecture, and real-world driving results prevent a meaningful performance ranking. 7

Li Auto: Li Auto’s 5 nm M100 has a reported 1,280 TOPS figure, giving it a disclosed throughput benchmark that Xiaomi has not supplied. 67

BYD: BYD’s 4 nm Xuanji A3 is reportedly already in mass production, so BYD holds an execution and deployment advantage even if D100’s claimed node is smaller. 6

XPeng: XPeng is likewise pursuing proprietary autonomous-driving silicon, making Xiaomi part of a wider Chinese EV-industry move to reduce reliance on merchant processors. Publicly comparable details remain uneven across these companies. 6

Nvidia and Tesla: Xiaomi’s current EVs have used Nvidia hardware, and D100 is positioned as a route to reduce that dependence from 2027. 11 Strategically, the effort resembles Tesla’s in-house FSD-computer approach: integrate vehicle software, data, models, and compute rather than buy the entire platform externally. Nvidia, however, remains the better-established supplier ecosystem and benchmark platform; Xiaomi has not released enough D100 performance, efficiency, software-toolchain, or safety-validation data to establish parity.

D100 specifications and claims: Xiaomi says the chip has a 20-core high-performance CPU, 16-core NPU, and support for up to 160 GB of unified memory. It says this enables local execution of AI models with up to 200 billion parameters. 12

Process-node claim: Xiaomi calls D100 mainland China’s first high-compute smart-driving AI chip built on a 3 nm process. That is Xiaomi’s claim; the company did not disclose a TOPS figure, the foundry, a first vehicle model, or a precise vehicle-installation timetable beyond planned 2027 commercialization. Consequently, its raw inference performance cannot yet be compared credibly with rivals’ published TOPS ratings. 1012

AI Cube demonstration: Xiaomi also showed a 150 W AI Cube Prototype combining three Xring chips: the O3 mobile SoC, O100 AI accelerator, and D100 automotive processor. The demonstrated unit reportedly had 80 GB unified memory and ran a local “120B + 3B” model configuration; it was an engineering prototype, not a commercial product announcement. 5

Nio: Its 5 nm Shenji NX9031 is already deployed in Nio and Onvo vehicles, with more than 300,000 units shipped; Nio has previously claimed over 1,000 TOPS per chip. D100’s 3 nm node is nominally more advanced, but Xiaomi’s undisclosed TOPS, power, bandwidth, safety architecture, and real-world driving results prevent a meaningful performance ranking. 7

Li Auto: Li Auto’s 5 nm M100 has a reported 1,280 TOPS figure, giving it a disclosed throughput benchmark that Xiaomi has not supplied. 67

BYD: BYD’s 4 nm Xuanji A3 is reportedly already in mass production, so BYD holds an execution and deployment advantage even if D100’s claimed node is smaller. 6

XPeng: XPeng is likewise pursuing proprietary autonomous-driving silicon, making Xiaomi part of a wider Chinese EV-industry move to reduce reliance on merchant processors. Publicly comparable details remain uneven across these companies. 6

Nvidia and Tesla: Xiaomi’s current EVs have used Nvidia hardware, and D100 is positioned as a route to reduce that dependence from 2027. 11 Strategically, the effort resembles Tesla’s in-house FSD-computer approach: integrate vehicle software, data, models, and compute rather than buy the entire platform externally. Nvidia, however, remains the better-established supplier ecosystem and benchmark platform; Xiaomi has not released enough D100 performance, efficiency, software-toolchain, or safety-validation data to establish parity.