AI Infrastructure Scales Up: High-Speed Interconnect Supply Chain Explodes
AI Infrastructure Reaches the Inflection Point for Scalable Deployment: High-Speed Interconnect Supply Chain Poised for Definitive Boom
Global demand for large-model training and inference is reshaping the evolution of computing infrastructure at an unprecedented pace. In Q1 2026, Dongshan Precision’s optical module revenue doubled year-on-year; Yuanjie Technology’s CW laser driver net profit surged 1,153%; Longsys’ revenue from next-generation interconnect chips—including CXL and MXC—grew 93.8%; and Zhaolong Interconnect announced a RMB 1.079-billion investment to expand its high-speed data transmission capabilities. The synchronized performance and capital expenditure surge across these four representative companies is no isolated signal—it marks a pivotal inflection point where AI compute infrastructure is transitioning decisively from technology validation to large-scale deployment. Spanning optical communications, electrical interconnects, protocol-stack chips, and system integration, this supply chain combines sustained high industry momentum, formidable technical barriers, and a clear, viable path for domestic substitution—making it today’s most definitive core theme within China’s A-share “hard tech” sector.
Optical Modules: 400G/800G Adoption Accelerating; Domestic Vendors Break Through the “Volume-Price Upward Spiral” Bottleneck
Optical modules form the physical-layer foundation for intra-cluster and cross-node data transmission in AI systems. As next-generation AI servers—such as NVIDIA’s GB200 NVL72—adopt 800G optical interconnect architectures, and cloud hyperscalers—including Microsoft and Meta—deploy 800G DR8/FR4 optical modules en masse in ultra-large-scale data centers, the industry is undergoing a generational leap from 400G to 800G. Dongshan Precision’s optical module revenue doubling in Q1 2026 confirms its deep integration into leading AI server vendors’ supply chains. Notably, this growth stems not merely from higher shipment volumes but also from product mix upgrades: 800G modules command unit prices 1.8–2.2× those of 400G modules, while presenting significantly higher technical hurdles—including silicon photonics integration and high-speed modulator packaging—boosting gross margins by 5–8 percentage points over the prior generation. Domestic vendors have now mastered in-house development of high-speed optical engines, with industry leaders—including Innolight, Eoptolink, and Dongshan Precision—achieving mass delivery of 800G modules; several are already advancing engineering samples of 1.6T modules. The optical module industry is shifting from cost-driven competition toward holistic competitiveness centered on performance, reliability, and delivery capability—continuously widening its moat.
CW Lasers: The Critical “Heart” of the Silicon Photonics Era—Yuanjie Validates Its Technological Scarcity
Continuous-wave (CW) lasers serve as the foundational light source for silicon photonic chips; their performance directly determines the power efficiency, bandwidth, and stability of optical interconnect systems. At speeds of 800G and beyond, conventional DFB lasers face limitations such as insufficient modulation bandwidth and temperature-induced wavelength drift. High-performance CW DFB lasers based on indium phosphide (InP) have thus become indispensable for silicon photonic transceivers. Yuanjie Technology’s Q1 2026 net profit soared 1,153%—driven primarily by rapidly expanding market share among leading silicon photonics solution providers. The company has achieved full-series mass production of 25G/50G CW DFB lasers and completed tape-out verification of its 100G CW laser, with stable yields exceeding 92%. Its technological moat rests on three pillars: precise wavelength control in epitaxial growth (±0.5 nm), ultra-low relative intensity noise (RIN < −155 dB/Hz), and exceptional reliability (MTTF ≥ 50,000 hours). With only a handful of global vendors—including II-VI, Lumentum, and Yuanjie—capable of volume production, CW lasers have evolved from optional components into strategic, mission-critical bottlenecks within the AI optical interconnect ecosystem.
CXL/PCIe Chips: The “Neural Hub” Enabling Memory Pooling and Heterogeneous Computing
As GPU cluster scale exceeds 1,000 accelerators, traditional PCIe bus bandwidth and memory coherency constraints become increasingly acute. The Compute Express Link (CXL) protocol—supporting memory-semantic access, cache coherency, and device memory sharing—has emerged as a key enabling technology for building AI supercomputers. Longsys’ 93.8% revenue growth from its CXL/MXC (Memory eXpansion Controller) products signals its successful expansion from DDR memory interface chip leadership into the high-speed interconnect arena. MXC chips pool DRAM resources across multiple servers into a single logical memory space, reducing KV Cache loading latency during large-model inference by over 40%. Longsys has already completed joint validation with Alibaba Cloud and Baidu Intelligent Cloud; its CXL 3.0 controller supports up to 64 GT/s and integrates hardware-level security isolation modules. This domain features exceptionally high technical barriers—requiring deep protocol-stack expertise (CXL.io/CXL.cache/CXL.mem), advanced SoC integration capabilities, and close collaborative development experience with CPU/GPU vendors. Globally, only a select few players—including Longsys, IDT (Renesas), and Rambus—possess proven volume-production capability.
High-Speed Interconnect Components: Value Migration from “Cables” to “System-Level Solutions”
Unlocking the full performance potential of optical modules and chips depends critically on underlying high-speed interconnect components. Zhaolong Interconnect’s RMB 1.079-billion investment in its “High-Speed Data Transmission & Connectivity Project”—designed to produce 18 million high-speed interconnect units annually—is far more than simple copper-cable capacity expansion. Its strategic focus areas include: active high-speed cables (AECs) supporting PCIe 6.0 (64 GT/s); high-voltage RF coaxial components engineered for liquid-cooled AI servers; and machine-vision-specific interconnect modules integrating signal-integrity compensation algorithms. These products must overcome complex challenges—including impedance matching, crosstalk suppression, and thermal management—at millimeter-wave frequencies. Developing a single 800G AEC cable requires an 18-month R&D cycle and over six months of certification. Zhaolong’s move signals a broader transformation among domestic vendors—from standardized connector suppliers to AI infrastructure system-level interconnect solution providers—marking a substantial upward shift in value-chain positioning.
The Foundational Logic Behind This Certainty: Structural Demand, Technical Depth, and Accelerated Domestic Substitution
The high certainty surrounding this supply chain reflects not short-term thematic speculation, but three irreversible trends:
First, the global AI compute arms race has entered the “infrastructure-first” phase. According to Synergy Research, the number of new hyperscale data centers built worldwide will rise 37% in 2026, with each averaging 1,200 GPU servers—creating structural, non-discretionary demand for 800G optical modules, CXL-based memory expansion, and high-speed copper interconnects.
Second, technological iteration follows a “spiral-upward” dynamic: rising optical module speeds compel CW laser upgrades; broader CXL adoption, in turn, demands higher-bandwidth interconnect components—reinforcing technical barriers across layers.
Third, geopolitical considerations and supply-chain security imperatives are accelerating domestic substitution. Indigenous AI chip ecosystems—including Huawei Ascend and Cambricon MLU—urgently require fully controllable interconnect solutions, offering Longsys, Yuanjie, Zhaolong, and others an unprecedented window for design-in. Against this backdrop, the contrast is stark: when Sungrow Power—a traditional new-energy leader—reported a 40.12% YoY net profit decline in Q1, AI infrastructure vendors collectively delivered results that vastly exceeded expectations. The signal of industrial realignment is unmistakable.
In summary, the high-speed interconnect supply chain for AI infrastructure has moved decisively beyond the technology-feasibility validation stage and entered its golden era of scalable commercial deployment. Optical modules, CW lasers, CXL chips, and high-speed interconnect components constitute a tightly integrated, self-reinforcing loop—mutually enabling and locking in one another—to build a wide, deep, and commercially robust moat. In an era where computing power equals national strength, the construction pace of this “digital highway” will not only determine the speed of China’s autonomous AI advancement—but also serve as a core benchmark for assessing the maturity of the nation’s next-generation information infrastructure.