Nvidia stock dips slightly as Samsung scales Groq AI chip production amid growing demand.
Groq’s energy-efficient inference chips are driving Nvidia’s strategic partnership with Samsung.
Increased AI chip demand pressures memory supply, impacting device margins and smartphone profits.
Nvidia may unveil new SRAM-based Groq inference chips at GTC 2026, analysts say.
Nvidia (NVDA) stock experienced a slight decline as investors reacted to the company’s move to increase production of Groq-designed AI inference chips through Samsung Electronics’ foundry division. The ramp-up comes amid surging demand for energy-efficient AI processors, particularly those optimized for inference tasks rather than training workloads.
Industry sources report that Samsung will boost wafer production for Groq chips from 9,000 units last year to 15,000 units this year. The chips will be manufactured on Samsung’s advanced 4-nanometer process, marking a significant increase in output. In addition to supporting Nvidia’s AI ambitions, Samsung will produce all processors for South Korea’s HyperAccel, another AI chip startup.
Groq, a U.S.-based AI chip startup backed by Nvidia through a technology licensing partnership, focuses on inference processing rather than traditional GPU-intensive training. Its Language Processing Units (LPUs) employ on-chip static RAM (SRAM) rather than high-bandwidth memory (HBM), enabling over 80 terabytes per second of bandwidth while consuming approximately ten times less energy than comparable GPUs.
NVIDIA Corporation, NVDA
By sticking with a 14-nanometer process and avoiding HBM, Groq avoids the supply-chain bottlenecks affecting GPU production. The current LPUs are designed, engineered, and manufactured entirely in North America, contrasting sharply with the global sourcing necessary for modern GPUs. Analysts say this strategy allows Nvidia to meet growing inference demands without relying on heavily constrained GPU supply chains.
The surge in AI chip demand is creating ripple effects across the broader electronics market. Memory shortages caused by increased AI chip production have affected parts used in personal computers and mobile devices. Samsung, benefiting from these trends, reported an operating profit increase of more than 200% year over year in Q4 2025, largely driven by its memory business.
However, other segments of Samsung’s business have been negatively impacted. The company’s mobile division saw operating profits fall to 1.9 trillion won, down 9.5% year over year, as rising component costs squeeze margins. Analysts caution that continued price pressures in memory and AI chip components may push electronics prices higher if manufacturers pass costs onto consumers.
Looking ahead, Nvidia is expected to unveil a new Groq-designed inference chip at its GTC 2026 event. Reports suggest the upcoming chip will utilize SRAM instead of HBM, further emphasizing energy efficiency and reduced supply-chain risk.
Investors and industry watchers are closely monitoring Nvidia’s strategic partnerships and product roadmap, with the market responding cautiously to both growth potential and near-term cost pressures.
The collaboration between Nvidia and Samsung underscores the growing importance of specialized AI inference processors in the semiconductor landscape. As demand for energy-efficient AI solutions rises, Nvidia’s approach of scaling production while avoiding traditional GPU bottlenecks may become a critical differentiator in the highly competitive AI chip market.
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