Here's what we know. 

The global AI chip market hits $40.79 billion in 2025, and NVIDIA $NVDA owns most of it. 

The company crossed a $5 trillion valuation in late October and will post more net income this year than $AMD and Intel's $INTC combined revenues. 

NVIDIA's market share sits at 86% for AI GPUs, up from 80% just months ago. 

The company will consume 77% of all wafers used for AI chips in 2025, jumping from 51% in 2024. That's 535,000 300-mm wafers flowing through TSMC's facilities. 

Morgan Stanley's data shows NVIDIA pulling further ahead while everyone else fights over scraps.

AMD holds roughly 11% of the data center AI chip market. 

Intel, despite its legacy, manages just 8.7% with its Gaudi 3 platform. 

Qualcomm hasn't shipped a single data center AI chip yet. 

The Blackwell GPU generation launched this year with the H200 Tensor Core achieving 4.2x speedup on large language model inference compared to the H100. 

OpenAI trained GPT using NVIDIA chips. 

Microsoft $MSFT, Meta $META, Amazon $AMZN, and Alphabet $GOOGL all run massive AI workloads on NVIDIA hardware.

But here's the thing. NVIDIA's dominance isn't just about silicon. 

The CUDA software platform locks customers into the ecosystem. Developers know CUDA. Enterprise IT teams trust CUDA. Switching costs are high. AMD's ROCm platform works, but it lacks maturity. 

Most companies won't risk their AI roadmap on an unproven alternative.

NVIDIA also controls the supply chain. 

The company secured more TSMC capacity than competitors, giving it first access to advanced nodes and CoWoS packaging. 

When demand exceeds supply, NVIDIA wins by default.

AMD's MI300X series offers competitive performance at lower prices. 

The company scored deals with Microsoft $MSFT, Oracle $ORCL, and OpenAI. 

Revenue from AI chips should hit $5.6 billion in 2025, doubling its data center footprint. The MI400 family promises 2.3x training speed improvements over MI300.

Yet AMD's Q3 2025 data center growth disappointed. 

The Trump administration blocked MI308 exports to China. 

Customers delayed purchases ahead of the MI350 launch in late 2025.

NVIDIA's H200 chips intensified competition. AMD gained ground but not fast enough.

The company still controls just 6% of the discrete GPU market while NVIDIA owns 94%.

Qualcomm announced the AI200 and AI250 chips in October 2025, marking its entry into data center AI. 

The AI200 ships in 2026 with 768 GB of LPDDR memory per card. The AI250 follows in 2027 with 10x higher memory bandwidth. Both target AI inference workloads where cost efficiency matters most.

$QCOM surged 11% on announcement day. Saudi Arabia's Humain committed to 200 megawatts of deployment. But Qualcomm faces challenges. The company has zero data center market share today. 

NVIDIA, AMD, and Intel have established relationships with cloud providers. Qualcomm's chips focus on inference, not training, limiting the addressable market.

The AI200 uses LPDDR memory instead of high-bandwidth HBM, reducing costs but also performance. Rack-scale systems consume 160 kilowatts, comparable to competitors. 

Qualcomm's track record in mobile gives it credibility on power efficiency. Whether that translates to data center success remains uncertain.

Intel announced Crescent Island, a new data center GPU targeting inference workloads. 

The chip features 160 GB of LPDDR5X memory and Xe3P microarchitecture optimized for performance per watt. Customer sampling begins in the second half of 2026.

Intel $INTC reported a $19 billion net loss in 2024. 

The U.S. government invested $8.9 billion for a 10% stake. NVIDIA invested $5 billion for 4% ownership, creating an unusual dynamic where competitors share equity. 

Gaudi 3 failed to gain traction after launch. Intel canceled its Falcon Shores accelerator to focus resources.

Crescent Island represents a fresh start. The chip targets air-cooled enterprise servers, avoiding expensive liquid cooling infrastructure. Intel's open software stack aims to reduce switching costs. 

But the company won't ship until late 2026 at earliest. By then, NVIDIA will have launched next-generation products. Intel needs flawless execution, and its recent history suggests that's unlikely.

The AI chip market will hit $165 billion by 2030. 

JPMorgan estimates custom chips from Google, Amazon, Meta, and OpenAI will capture 45% of the AI chip market by 2028, up from 40% in 2025. 

Google's TPU v7 Ironwood launched this year. Amazon's Trainium chips power internal workloads. Microsoft developed Maia accelerators. 

These companies want to escape NVIDIA's pricing power and supply constraints.

Google has sold TPUs to external cloud providers, testing demand outside internal use cases. 

The total addressable market grows fast enough that NVIDIA can maintain high revenue even as its share declines.

NVIDIA's advantages compound. 

Market share drives volume, which funds R&D, which creates better products, which drives more market share. 

The CUDA ecosystem grows stronger as more developers build expertise. Supply chain priority follows from being TSMC's largest customer.

Competition intensifies. AMD closes the software gap gradually. Qualcomm brings mobile efficiency expertise. 

Intel leverages its x86 CPU dominance and government backing. Custom silicon reduces reliance on merchant chips. 

But none of these factors will dethrone NVIDIA in the next 24 months.

The company should maintain 70-80% market share through 2026. Margins will compress slightly as competition increases. AMD might reach 15% share by late 2026 if the MI400 delivers on promises. Qualcomm and Intel need multiple product cycles to gain meaningful traction.

NVIDIA's greatest risk isn't competition. 

It's market saturation if AI growth slows or companies realize current infrastructure exceeds near-term needs. That hasn't happened yet. 

Data center capEx keeps accelerating. As long as demand stays strong, NVIDIA has the capacity, ecosystem, and execution to remain dominant.