Broadcom's AI Inference Chips Emerge as Nvidia's Complement

Investors seeking exposure to artificial intelligence have flocked to Nvidia, the dominant supplier of data center GPUs used to train large language models. But focusing solely on training infrastructure means missing the equally critical inference market—where Broadcom has established a commanding position.

The training-inference divide

Nvidia's GPUs excel at the computationally intensive work of training AI models, processing vast datasets to build the neural networks that power today's AI applications. The company's CUDA software ecosystem and proprietary tooling have created deep customer lock-in among the world's leading AI developers.

Inference represents the other half of the equation: the process of actually running those trained models to generate responses, analyze data, or make predictions. At scale, this workload demands different optimization trade-offs than training.

Broadcom has carved out dominance in custom application-specific integrated circuits (ASICs) designed specifically for inference tasks. These chips can process inference workloads faster and more cost-efficiently than general-purpose GPUs when deployed at hyperscale. Meta, Google, OpenAI, and Anthropic all rely on Broadcom's custom accelerators to power their AI applications, according to reporting by The Motley Fool.

Why it matters

The AI infrastructure market is bifurcating into two distinct segments with different technical requirements and economics. Companies building AI services need both training capacity and inference deployment at scale. Broadcom's fiscal 2025 AI chip revenue reached $20 billion—31% of total revenue—and the company projects that figure will approach $115 billion by fiscal 2027, representing nearly two-thirds of anticipated total revenue. That trajectory suggests inference workloads are scaling as rapidly as training infrastructure.

Comparative growth and valuation

From fiscal 2025 through fiscal 2028, analysts project Broadcom's revenue will grow at a 62% compound annual rate, with earnings per share expanding at 77% annually. Nvidia's growth forecast from fiscal 2026 through fiscal 2029 shows 59% annual growth for both revenue and earnings.

Despite comparable or superior growth rates, Broadcom trades at 22 times forward earnings compared to Nvidia's 23 times multiple. The valuation gap is narrow, but Broadcom's faster earnings growth and lower multiple create a compelling relative value proposition.

Nvidia continues integrating inference capabilities into its latest GPU architectures, but the company remains primarily associated with training workloads. For investors wanting comprehensive AI infrastructure exposure, owning both companies captures the full stack from model development through production deployment.

These details were first reported by Leo Sun at The Motley Fool.