Nvidia Trades at 24.5 P/E and Sub-0.7 PEG Despite 62% Revenue Surge
Nvidia shares trade at a forward P/E of 24.5 and a PEG ratio below 0.7 despite 62% revenue growth to $57 billion last quarter, up from $5.9 billion in Q3 2023. Its data center networking revenue surged 162% to $8.2 billion, and recent acquisitions of SchedMD and a Groq inference deal strengthen its AI moat.
1. Attractive Valuation Despite Market Leadership
Nvidia’s stock begins 2026 trading at a forward price-to-earnings ratio of 24.5x based on analyst estimates for its fiscal 2027 year ending January 2027, and its price/earnings-to-growth ratio stands below 0.7x. PEG ratios under 1x are widely regarded as undervalued, suggesting Nvidia’s share price does not fully reflect its rapid growth trajectory. This valuation level is especially notable given the company’s market-leading position in AI infrastructure and data centers.
2. Explosive Revenue Expansion in Data Centers
In the most recent quarter, Nvidia reported revenue of $57 billion, marking a 62% sequential increase and nearly a tenfold rise from the $5.9 billion generated in fiscal Q3 2023. Within its data center business, networking solutions driven by NVLink interconnects saw revenue surge 162% year-over-year to $8.2 billion. This outsized growth underscores the critical role of its GPUs and networking stack in powering large-language-model training and high-performance computing workloads.
3. Strengthening Moat Through Software and Partnerships
Nvidia’s CUDA software platform remains the dominant development environment for AI workloads, with most foundational AI frameworks optimized for its architecture. The recent acquisition of SchedMD, creator of the Slurm open-source cluster manager, further integrates job scheduling and resource optimization into Nvidia’s ecosystem for hyperscalers. Additionally, Nvidia has licensed inference technology from Groq and struck a talent partnership to embed specialized inference chips into its CUDA fabric, positioning it to defend against custom ASIC competitors and broaden its AI product suite.
4. Growth Prospects and Competitive Position
Analysts project that demand for AI infrastructure will continue to accelerate through 2026 and beyond, driven by enterprise cloud build-outs and on-premise deployments. While custom AI ASICs offer efficiency gains for narrowly defined tasks, they lack the flexibility of GPUs to adapt to evolving AI models. Nvidia’s roadmap includes next-generation GPU architectures and the Rubin CPU-GPU fusion platform on 3nm process nodes, initiatives expected to sustain revenue compound annual growth rates above 40% over the next two fiscal years.