Broadcom stock (NASDAQ: AVGO) is suddenly looking like the AI name Wall Street may have underestimated.
The market value of the company is above $2 trillion, its stock has hit a record high, and the company is guiding AI revenue sharply higher into 2026.
That makes the comparison with Nvidia especially insightful, as Broadcom is taking a distinct approach instead of going head-to-head in the GPU market.
It is building a different lane in custom AI chips, networking, and software.
For investors, the real question is whether Broadcom is still under-appreciated, or whether the market has already caught up.
Numbers that tell the real story
Broadcom’s latest quarter did not just look good; it looked like a company entering a new phase of scale.
The company said first-quarter AI revenue reached $8.4 billion, up 106% from a year earlier, and it guided second-quarter AI semiconductor revenue to $10.7 billion.
Broadcom also said it has a $73 billion AI backlog scheduled to ship over the next 18 months.
Nvidia is still growing fast, but it is doing so off a much larger base: fiscal 2026 revenue rose 65% to $215.9 billion, while data-center revenue climbed 68% to $193.7 billion.
All growth comparisons below are forward projections, not trailing reported figures.
That distinction matters because analysts expect Broadcom’s growth to compound at a slightly faster pace over the next two years.
MetricBroadcomNvidiaAI revenue growth$8.4B in Q1 FY26, up 106% YoYFY26 revenue up 65%; data-center revenue up 68%Forward P/EAround 41x on analyst-based screensAbout 24.5x forward earnings2-year projected growth147%124%
The backdrop is still very much an AI spending boom.
The company’s CEO, Hock Tan, said Broadcom has “line of sight” to over $100 billion in AI chip revenue by 2027.
That makes Broadcom a major player as Deloitte expects the global semiconductor market to reach $975 billion in 2026, up 26% from 2025.
Also read: Nvidia is quietly betting 8% of its portfolio on this $10 stock
Why are Broadcom chips different?
The Broadcom story is not really about replacing Nvidia in every job; it is about a different kind of chip.
Nvidia sells general-purpose GPUs that can handle a wide range of AI tasks.
Broadcom builds custom ASICs, or XPUs, that are designed for a specific hyperscaler and a specific workload.
The chips are described as custom processors tailored for a single function, which is exactly why cloud giants like Google and Meta keep turning to them for large-scale AI deployments.
That shift matters because AI spending is moving from training giant models to running them efficiently in the real world.
Inference is where custom silicon can shine, especially when customers want tighter control over cost, power use, and supply.
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