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Time of India

Jensen Huang may have met his match, and it's not AMD, but a stealthy South Korean challenger

Who is FuriosaAI, and why are they suddenly in the spotlight? What makes FuriosaAI's chip so special? Live Events Custom-built for AI inference : Unlike Nvidia's general-purpose GPUs, RNGD is optimized solely for AI workloads. : Unlike Nvidia's general-purpose GPUs, RNGD is optimized solely for AI workloads. 5nm process with HBM3 memory : This enables faster performance with lower energy consumption. : This enables faster performance with lower energy consumption. Massive efficiency gains: LG AI Research found that RNGD delivered 2.25x faster inference per watt compared to traditional GPUs. LG AI Research just gave FuriosaAI a massive boost Why did Meta try to buy FuriosaAI? Is FuriosaAI really a threat to Nvidia? Feature FuriosaAI RNGD Nvidia H100 Architecture Custom AI inference NPU General-purpose GPU Process TSMC 5nm TSMC 4nm Memory 48GB HBM3 80GB HBM3 TDP ~180W ~700W Inference efficiency 2.25x GPU per watt Industry benchmark Target use case LLM inference Training + inference What does this mean for the global AI chip market? FuriosaAI's edge lies in energy efficiency, affordability, and regional backing. lies in energy efficiency, affordability, and regional backing. Nvidia's strength remains raw performance and broad developer support. remains raw performance and broad developer support. Meta's pivot toward in-house chips signals a growing trend toward vertical integration in AI. Could FuriosaAI disrupt Nvidia's AI dominance? FAQs: Nvidia vs FuriosaAI: (You can now subscribe to our (You can now subscribe to our Economic Times WhatsApp channel For years, Nvidia CEO Jensen Huang has reigned supreme in the AI chip world. Despite fierce competition from AMD and Intel, Nvidia's dominance in training and running large language models has gone largely unchallenged—until now. A stealthy South Korean startup,, is making waves in the global semiconductor scene and may just be the first true threat to Nvidia's AI hardware in 2017 and backed by heavyweights like Samsung Electronics and Naver Corp,has flown under the radar for years. But in 2025, the startup shocked the tech world by turning down an. That rejection alone signaled confidence—but the real attention came when FuriosaAIInstead of selling, FuriosaAI chose to go big. And now, they're emerging as a serious AI accelerator powerhouse—exactly the kind of challenger Nvidia hasn't faced from Asia until the heart of FuriosaAI's rise is its new, a next-gen AI inference accelerator built to handle the kind of large-scale models powering everything from ChatGPT-style tools to enterprise what sets RNGD apart:That kind of power-to-efficiency ratio could be a game-changer—especially for companies scaling AI operations while trying to manage rising power and cooling biggest breakthrough yet came when LG AI Research announced it would integrate RNGD chips into its EXAONE platform, the large-scale AI system used for research across biotech, telecom, and FuriosaAI, this deal is more than a commercial win—it's validation. LG's evaluation didn't just show superior power efficiency. It also demonstrated better cost-performance compared to Nvidia's popular H100 chips, which are the backbone of today's AI data other words: FuriosaAI just proved it can compete—and maybe outperform—the world's most dominant AI failed $800 million bid for FuriosaAI speaks volumes. The social media giant, which is investing billions into building its own generative AI systems, clearly saw value in acquiring a company with proprietary AI the deal reportedly fell apart not over price—but. FuriosaAI wanted to stay independent and pursue partnerships with global enterprises instead of becoming a Meta-only Meta is also, and is reportedly testing it through Taiwan's TSMC. However, the company's recent friction with Nvidia (Meta was notably excluded from Blackwell GPU order announcements) may have accelerated its chip-buying be clear: Nvidia is still the king of the hill. The company's H100 and upcoming Blackwell chips are powering almost every major AI deployment, from OpenAI to Amazon to FuriosaAI represents something different—a, efficiency-optimized challenger built outside of Silicon Valley. And as, especially at scale, companies will start looking beyond Nvidia for FuriosaAI isn't aiming to replace Nvidia across the board—but it's carving out a crucial niche in, which is where AI applications go from test labs to real-world race is officially heating up. With Meta, Microsoft, Amazon, and other Big Tech players pushing to reduce their reliance on Nvidia, there's enormous demand forThis competitive shake-up is especially notable because South Korea has long been seen as a memory chip superpower—not a leader in AI accelerators. FuriosaAI's rise could reshape the semiconductor narrative, adding a powerful new player to the global AI arms Jensen Huang has faced plenty of rivals before—Intel, AMD, Google TPU—but few with the underdog precision and strategic clarity of FuriosaAI. With top-tier backing, an efficient and powerful chip design, and validation from a major global enterprise like LG, this South Korean startup is signaling that it's ready for the big it's enough to dethrone Nvidia remains to be seen. But one thing is clear: Jensen Huang may have finally met his match—and it's not AMD, but a stealthy South Korean is a South Korean chip startup that makes powerful AI chips, and it's now gaining attention for offering faster, more energy-efficient alternatives to Nvidia's AI RNGD chip delivers overthan Nvidia's GPUs, using less power and offering better cost performance for AI turned down Meta's offer because it wanted to stay independent and pursue its own vision of working with global partners like uses FuriosaAI's chips to run its large language models (LLMs) for research in industries like biotech, telecom, and especially for companies focused on AI inference tasks. FuriosaAI offers a cost-effective, energy-efficient alternative that's catching global is backed by major South Korean players like Samsung Electronics and Naver Corp, giving it strong support for global chips are built for—the part where models are used in real applications, not just entirely, but it could carve out a large share of the, especially where power efficiency matters like telecom, research, biotech, and finance are already testing or using FuriosaAI chips in real-world AI FuriosaAI just signed a big deal with LG after rejecting Meta's offer, proving it's ready to compete with the biggest names in AI.