Xiaomi has launched its latest XRING O3 along with XRING O100 and XRING D100, and an AI Cube Prototype.
XRING O3 is made with a 3nm node and features 10-core all-big-core CPU along with 16-core GPU. It also features the industry’s first LPDDR6 DRAM in smartphone SoC.
XRING O100 is Xiaomi’s AI accelerator chip, 6nm base with 3D wafer-level stacking; XRING D100 is an automotive SoC built on a 3nm process with a 20-core CPU and 16-core NPU architecture.
Xiaomi also showcased the AI Cube, combining XRING O3, XRING O100, and XRING D100, into a 150W prototype mini-PC.

Xiaomi Technology’s latest XRING entails more than just a new smartphone chip. The launch highlights Xiaomi's broader strategy of developing in-house silicon across smartphones, AI, intelligent driving and its wider human-car-home ecosystem.

Xiaomi's first attempt at developing smartphone SoCs dates back to the Surge S1 in 2017, but the effort did not scale into a sustained smartphone chipset business. The launch of the XRING O1 in 2025 marked Xiaomi's return to in-house smartphone silicon. Just over a year later, Xiaomi is expanding beyond smartphone SoCs into AI acceleration and intelligent driving.

XRING O3

XRING O3 features some breakthroughs, with 10-core all-big-core CPU architecture featuring 2x C1-Ultra + 4x C1-Premium + 4x C1-Pro and is built on TSMC’s 3nm node. Another major improvement is that it features 16-core G2-Ultra NX GPU delivering major GPU performance enhancement as compared to its competitors. The world's first smartphone SoC to support LPDDR6, with 10667 Mbps memory speed and 113.8GB/s memory bandwidth.

Key Parameters:

Process Node: 3nm TSMC
CPU: 10-core all-big-core
GPU: 16-core G2-Ultra NX – 85% peak performance, 182% ray tracing improvement, and up to 64% lower power as compared to previous generation; 8 integrated NX neural accelerators (3.2K/120fps hardware frame interpolation).
NPU: 4-core low-power architecture; 200 TOPS tensor at A8W4 precision; 3.13 TFLOPS vector.
Memory: First SoC to support LPDDR6 with 10,667 Mbps speed and 113.8 GB/s; 60 MB system-level cache.

Comparison Between XRING O3 and XRING O1

Expected Timeline: The XRING O3 will feature in the Xiaomi 18-Fold, which is likely to launch in September, and the Xiaomi Pad 9 Pro Max, which is likely to launch in Q4 2026.

XRING O100

The XRING O100 is the first AI-accelerator from Xiaomi. It vertically stacks a 6nm NPU compute wafer with dual high-speed DRAM memory wafers (Wafer-to-Wafer 3D Stacking), and uses advanced hybrid bonding, it is paired with Xiaomi’s in-house designed high-bandwidth matrix bus and features 14-core NPU with 1.22 TB/s memory bandwidth and up to 330 token/s edge inference on a 3B parameter model. The O100's wafer-on-wafer hybrid bonding at 1.4 μm pitch is among the major highlights, as it offers HBM-class bandwidth through advanced packaging on a mature 6nm node. XRING O100 is designed for on-device edge AI applications for devices including smartphones, PCs, robots, EVs, AI Cube.

Key Parameters:

Architecture: 14-core NPU array; high-bandwidth matrix bus
Packaging: 6nm with 3D wafer-level stacking; Wafer-on-Wafer advanced packaging, hybrid bonding at 1.4 μm bond pitch, 28,672 effective data lines
Memory Bandwidth: 1.22 TB/s near-memory computing bandwidth
Performance: 330 TPS on-device inference (Xiaomi lab)

XRING D100

Built on a 3nm process with a 20-core CPU and 16-core NPU architecture, the XRING D100 is designed to deliver high-performance AI computes for vehicles, featuring up to 160GB unified memory and can deploy 200B parameter on-device model.

AI Cube

Xiaomi also showcased the AI Cube, an NPU-based engineering prototype mini-PC that combines the XRING O3, XRING O100 and XRING D100. The system supports local deployment of Xiaomi’s 120B and 3B MiMo models, with fast/slow system switching and up to 150W of sustained performance.

The AI Cube could serve as an entry point for Xiaomi’s broader AI ambitions, providing a platform to optimize applications around its MiMo models and explore new AI use cases. It could also support Xiaomi’s broader smartphone-to-car strategy by extending its in-house silicon capabilities beyond smartphones.

By bringing memory and compute closer together, the XRING O100 can potentially improve data-movement efficiency and reduce memory bandwidth bottlenecks in bandwidth-intensive AI and LLM workloads. This architecture could also give Xiaomi greater control over its hardware-software stack and create opportunities to reduce its reliance on third-party compute platforms.

Over time, Xiaomi could integrate its in-house chipsets across a broader range of devices, potentially reducing its dependence on third-party hardware platforms and improving cost efficiency and margins, although the extent of these benefits will depend on scale, yields, software maturity and overall chip development costs.

From Smartphone to AI: Xiaomi’s Shift Toward a Multi-domain AI Chip Ecosystem

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