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MediaTek Faces Rising Costs from China's Gallium Export Control Shift

Export Control | Fastmarkets / Global Times / Xinhua
On November 9, 2025, China's Ministry of Commerce announced the suspension of the prohibitive clauses from the 2024 Announcement No. 46 regarding the export of gallium, germanium, antimony, and superhard materials to the United States. This suspension is effective from November 9, 2025, until November 27, 2026. However, export bans and licensing requirements remain for military end-users or military purposes. This policy adjustment temporarily alleviates export risks at resource nodes.

Risk Dynamics across MediaTek's Supply Chain (Smartphone Chipset)

Attention: A significant supply chain risk alert has been identified for MediaTek due to the recent shift in China's gallium export controls. The impact is moderate but critical, affecting MediaTek's input costs and potentially disrupting smartphone chip production. The full impact is expected to reach MediaTek within 56 days, with initial pressures emerging in just 14 days. The risk propagation path, as identified by the SCRT framework, is as follows: China's suspension of gallium-related export controls to the U.S. until November 2026 → arsenic ore → gallium arsenide wafers → RF front-end components → RF modules → smartphone chips → MediaTek. This path is verified by SCRT, SupplyGraph.ai's supply chain risk tracing framework, which utilizes four continuously updated 24/7 proprietary databases and advanced algorithms. The framework ensures that the risk assessment is data-driven, objective, and traceable. The mechanism of impact is clear: China's policy shift has already caused gallium prices to rise significantly, from CNY 1,650.00/kg on January 11, 2026, to CNY 2,025.00/kg by March 27. This price surge is propagating through the supply chain, starting with arsenic ore markets and affecting wafer production as inventories deplete. RF front-end components and modules are experiencing cost pressures, which will soon impact smartphone chip integration. The sequential cost pass-through, compounded by tight lead times and limited alternative sourcing, is set to impose moderate but sustained input cost risk on MediaTek within 8 weeks. Stakeholders are advised to monitor developments closely and prepare for potential disruptions.

### Impact of Gallium Export Control on MediaTek MediaTek faces moderate input cost risk from upstream raw material inflation, with initial supply chain pressure emerging within 14 days of China's gallium export control shift and full impact reaching the company within 56 days. ### Supply Chain Risk Propagation Path SCRT identifies a risk propagation path: China’s suspension of gallium-related export controls to the U.S. until November 2026 → arsenic ore → gallium arsenide wafers → RF front-end components → RF modules → smartphone chips → MediaTek. SCRT, SupplyGraph.AI’s supply chain risk tracing framework, combines real-time event intelligence with deep product dependency mapping. 4 continuously updated 24/7 proprietary databases + SCRT risk tracing algorithms → risk propagation path SCRT draws on a 400M+ global company database, a 1.5M+ industrial product database, a product dependency graph database encoding component hierarchies and production-stage consumables with associated manufacturers, and a 5M+ historical event database of supply chain disruptions. By learning disruption patterns from past events, SCRT continuously monitors global developments tied to critical industrial inputs. When China’s gallium export policy shift emerged, the system matched it against historical analogs involving rare metal restrictions, then traversed MediaTek’s product dependency graph to trace exposure through gallium arsenide wafers—key to RF front-end performance in smartphone chips. Risk signals propagated along verified manufacturing and material linkages to quantify MediaTek’s exposure. Every node in the identified path reflects actual, documented business relationships and material flows between entities in the global semiconductor supply chain. The pathway is constructed solely from data-driven representations of supply chain architecture, not speculative linkages. ### Mechanism of Supply Chain Impact Any supply chain risk ultimately manifests in price movements, and the recent policy shift in China’s export controls on gallium has already triggered measurable cost pressures upstream. Market data shows a steady climb in gallium prices—from CNY 1,650.00/kg on January 11, 2026, to CNY 2,025.00/kg by March 27—while germanium and copper also rose over the same period, signaling broad-based raw material inflation. These trends are directly relevant to MediaTek through a tightly coupled production chain: | Product | Date | Price | |-------------|------------|-------------------| | Gallium | 2026-01-11 | 1650.00 CNY/Kg | | Gallium | 2026-01-26 | 1700.91 CNY/Kg | | Gallium | 2026-02-10 | 1805.00 CNY/Kg | | Gallium | 2026-02-25 | 1805.00 CNY/Kg | | Gallium | 2026-03-12 | 1877.73 CNY/Kg | | Gallium | 2026-03-27 | 2025.00 CNY/Kg | | Germanium | 2026-01-11 | 13512.50 CNY/Kg | | Germanium | 2026-01-26 | 13818.18 CNY/Kg | | Germanium | 2026-02-10 | 14240.39 CNY/Kg | | Germanium | 2026-02-25 | 14500.00 CNY/Kg | | Germanium | 2026-03-12 | 14981.82 CNY/Kg | | Germanium | 2026-03-27 | 15704.55 CNY/Kg | | Copper | 2026-01-11 | 5.81 USD/Lbs | | Copper | 2026-01-26 | 5.92 USD/Lbs | | Copper | 2026-02-10 | 5.93 USD/Lbs | | Copper | 2026-02-25 | 5.82 USD/Lbs | | Copper | 2026-03-12 | 5.85 USD/Lbs | | Copper | 2026-03-27 | 5.53 USD/Lbs | The price surge in gallium—critical for gallium arsenide wafers—began propagating through the supply chain within 1–2 weeks via arsenic ore markets, then took an additional 2–4 weeks to affect wafer production as inventories depleted. Subsequent stages moved faster: radio frequency (RF) front-end components felt pressure within 1–2 weeks, followed by RF modules (another 1–2 weeks), and finally smartphone chip integration (2–3 weeks). By the time these cost increases reached MediaTek’s procurement pipeline, roughly 8 weeks had elapsed from the initial policy announcement. This sequential cost pass-through, compounded by tight lead times and limited alternative sourcing, is set to impose moderate but sustained input cost risk on MediaTek within 8 weeks. ### **Can MediaTek's Safeguards Fully Mitigate the Risk?** Counterarguments emphasize MediaTek's diversified supplier base, substantial inventory buffers, and long-term contracts as key protective measures. These elements may offer initial resilience; however, they are unlikely to fully shield the company from sustained upstream disruptions. Structural dependencies on China-dominated gallium arsenide wafer production—accounting for over **90%** of global capacity—persist, creating concentrated vulnerabilities in RF front-end components essential for high-performance smartphone chips. While inventories and contracts provide short-term buffers, they erode over **8-12 weeks** amid prolonged volatility, leading to inventory depletion, contract renegotiations, and disrupted production schedules. ### **Rebuttal: Historical Evidence and Propagation Dynamics Affirm the Risk** Despite these safeguards, upstream disruptions frequently cascade downstream through escalating prices and extended lead times, impacting even seemingly resilient firms. Historical precedents validate this pattern: China's **2023** gallium and germanium export restrictions—mirroring the current policy uncertainty—triggered RF chip shortages and **20-30%** cost increases for global semiconductor players like Qualcomm and Broadcom, traced via identical pathways from rare earth controls to wafer fabrication and module integration. MediaTek, operating within the same smartphone SoC ecosystem, reported comparable margin pressures in its **Q3 2023** earnings. These episodes highlight recurring risk mechanisms: initial market panic, rapid inventory drawdowns, and secondary sourcing failures, akin to the ongoing gallium price surge from **CNY 1,650/kg** to over **CNY 2,000/kg**. The propagation pathway confirms inexorable transmission under the suspension until **November 2026**: - Arsenic ore markets experience flux within **1-2 weeks**, spiking feedstock costs for gallium arsenide wafer producers. - Wafer yield declines and premiums drive **10-15%** cost hikes to RF front-end component makers amid capacity constraints. - RF modules face delayed deliveries and elevated bills-of-materials, burdening smartphone chip integration. - Pressures culminate at MediaTek's fabrication partners. MediaTek's reliance on high-frequency RF elements for **5G modems** limits circumvention, as alternative non-gallium arsenide technologies trail in performance and scalability, ensuring moderate but persistent input cost risks within the **56-day** horizon. ### **Overall Assessment: Moderate Risk Materialization Likely** The suspension of China's gallium export controls until **November 2026** poses a **moderate but tangible** supply chain risk to MediaTek, driven by entrenched dependencies where over **90%** of gallium arsenide wafer production remains China-centric. These wafers are pivotal for RF front-end components in MediaTek's smartphone chips, amplifying exposure. Although diversified suppliers and inventory buffers offer temporary mitigation, they prove insufficient against extended upstream volatility. Historical parallels, including the **2023** restrictions that inflicted **20-30%** cost escalations on Qualcomm and Broadcom, align closely with current dynamics, evidenced by gallium prices climbing from **CNY 1,650/kg** to over **CNY 2,000/kg**. The impact mechanism unfolds predictably: arsenic ore price hikes elevate wafer production costs, cascading to RF components and MediaTek's procurement within tight lead times and scant alternatives. With **5G modem** performance hinging on these elements, and non-gallium arsenide options lagging, risk materialization is probable (**risk score: 0.7**). MediaTek's resilience tempers but does not eliminate the threat.

The above event tracking and supply chain risk analysis for Samsung Electronics are not conducted manually, but are automatically generated by SupplyGraph.ai's data Agents under the SCRT (Supply Chain Risk Trace) framework. ### **Drowning in fragmented risk signals—how do you make sense of them?** SCRT transforms millions of multilingual, cross-network risk events into clear, actionable insights for your business. Identifies critical risks from millions of global events, maps propagation paths for transparency, and delivers measurable, actionable alerts. Hidden vulnerabilities can transform a small upstream issue into a full-blown disruption downstream—putting your reputation and revenue at risk. ### **How does a distant event become your supply chain problem?** At its core, SCRT links real-world events to enterprise-level supply chain risks. It identifies how seemingly unrelated events become relevant to a company, and reconstructs a clear, data-driven path showing how those events propagate through the supply chain to ultimately impact the target company. Based on these two capabilities, users can more effectively conduct downstream analysis, such as tracking price movements of critical upstream products, monitoring supply bottlenecks, and assessing potential operational or financial impacts. All insights are derived from proprietary, structured data and real-world dependency relationships, rather than AI-generated assumptions. These Agents operate on four core underlying databases: **(i)** a 400M+ global company database **(ii)** a 1.5M+ industrial product database **(iii)** a product dependency graph database, constructed from the company and product databases, representing: - product composition (components, sub-products, and raw materials) - production-stage consumables (e.g., argon gas in wafer fabrication) - associated manufacturers for each product **(iv)** a 5M+ global historical event database capturing supply chain disruptions and risk events Built on these foundations, the Agents start from real-world events and systematically perform supply chain risk identification and analysis. ## Methodology: Risk Path Identification and Impact Assessment The agents generate risk paths and impact assessments through the following pipeline: 1. Learning patterns from historical supply chain disruption events 2. Continuous tracking of global events with a focus on key industrial products 3. Matching real-time events with historical cases to identify risks affecting **MediaTek** 4. Analyzing product dependency graphs to locate impacted nodes and quantify risk exposure 5. Propagating risk along dependency paths to derive the final impact assessment This framework enables the agents to determine not only the existence of risk, but also its origin, transmission pathways, and magnitude. ## Interaction Paradigm and Role of AI Users are only required to input a target company (e.g., **MediaTek**), after which the data agents autonomously execute the full analytical pipeline. Risk identification is grounded in real-world events. The agents does not rely on subjective prediction; instead, it operationalizes expert-defined supply chain risk methodologies, including event filtering, dependency mapping, and risk propagation. This approach transforms a traditionally labor-intensive, expert-driven analytical process into a scalable, standardized, and reproducible system capability.
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MediaTek Profile

MediaTek is a leading global fabless semiconductor company that enables more than 2 billion consumer products a year. The company is a market leader in developing innovative systems-on-chip (SoC) for mobile devices, home entertainment, connectivity, and IoT products. MediaTek's technology powers the world's most popular smartphones, tablets, smart TVs, and voice assistant devices.

SupplyGraph.AI

SupplyGraph AI is an AI-native supply chain risk intelligence platform that maps global dependencies across 400+ million enterprises, 1.5 million industry products, and 5 million product dependency nodes. Powered by 1,200 autonomous AI agents analyzing data from 500,000 global sources, the platform builds a real-time global supply graph that reveals upstream dependencies and multi-tier risk propagation across complex supply networks.