Broadcom vs AMD: Which is the Most Promising AI Chip Stock to Bet on After Nvidia?

marsbitPubblicato 2026-06-09Pubblicato ultima volta 2026-06-09

Introduzione

Amidst Nvidia's dominance in the AI chip market, Broadcom and AMD are key contenders for the second-place spot. AMD competes directly in general-purpose GPUs, gaining some traction with clients like Meta but facing significant challenges overcoming Nvidia's entrenched CUDA software ecosystem. In contrast, Broadcom pursues a differentiated strategy by designing custom XPU chips tailored to specific AI workloads for major clients like Anthropic, Google, Meta, and OpenAI. This approach offers efficiency advantages and greater customer stickiness, particularly as AI compute shifts from training to inference. Despite a recent stock sell-off following a Q2 revenue guidance miss, Broadcom's CEO reaffirmed the long-term target of $100 billion in annual AI chip revenue by fiscal 2027. With Q2 AI revenue at $10.8 billion, significant growth potential remains as its custom chip projects ramp up. While Broadcom trades at a higher valuation multiple than AMD, analysts argue this premium is justified given its superior competitive positioning and expected faster growth trajectory, making it the more compelling investment choice following its recent pullback.

Author: Justin Pope

Compiled by: Tide Research

Introduction: Beyond Nvidia, the battle for the runner-up position in AI chips is heating up. AMD has chosen to directly challenge Nvidia's general-purpose GPU path, while Broadcom takes a differentiated approach with custom chips (XPU), securing top clients like Anthropic, Google, Meta, and OpenAI.

Following the latest earnings report, Broadcom's stock price fell sharply, but the CEO still maintains the target of reaching $100 billion in annual AI chip revenue by fiscal year 2027. Motley Fool analyst Justin Pope believes that even though Broadcom is more expensive, this premium is worth paying.

Caption: Source Getty Images

Nvidia still firmly holds the top spot in the AI data center chip market. But the AI pie is simply too large, making the runner-up position equally valuable. According to Statista estimates, the AI chip market will grow to $333 billion by 2030.

This means other companies also have the opportunity to make investors a lot of money. Broadcom (AVGO, down 7.49% on the day) and AMD (down 11.01% on the day) are the two most competitive candidates. Both companies have made progress in the AI chip field, but overall, one is clearly more worthy of holding than the other.

AMD Chose a More Difficult Path

The core question is: How can a smaller company compete for market share with an industry giant?

AMD's strategy is to compete head-on with Nvidia in the field of general-purpose AI chips. To be fair, it has indeed achieved some results. Q1 2026 data center revenue grew 57% year-over-year to $5.8 billion.

AMD benefits from AI hyperscalers' natural desire not to put all their eggs in Nvidia's basket. AMD recently announced it will supply Meta with 6 GW of Instinct GPUs, with the first GW being a custom version.

But AMD is unlikely to truly threaten Nvidia's dominance. Meta and other Nvidia customers are deeply entrenched in Nvidia's CUDA software ecosystem. The moat of CUDA cannot be crossed by hardware specifications alone.

Broadcom's Custom Chip Path is the Winner

To breach Nvidia's moat, one must take a different path. Broadcom has achieved this with its XPU chips.

Unlike AMD, which emphasizes general-purpose AI chips, Broadcom tailors chips to each customer's specific AI workloads. This approach brings efficiency advantages and makes customer relationships stickier. Currently, Broadcom is designing custom chips for companies like Anthropic, Alphabet (Google's parent company), Meta, and OpenAI.

As computing demand shifts from training to inference, efficiency becomes even more critical, further amplifying the advantages of custom chips.

Following the latest Q2 earnings report, Wall Street heavily sold off Broadcom, mainly due to Q3 AI revenue guidance falling short of expectations. But CEO Hock Tan reiterated on the earnings call that the company's long-term expectation of reaching $100 billion in annual AI chip sales by fiscal 2027 remains unchanged. Q2 AI revenue was $10.8 billion, and there is still significant growth potential as custom chip projects ramp up.

You Get What You Pay For

With a roster of top-tier AI clients and steady progress toward the $100 billion annual revenue target, Broadcom indeed has a stronger competitive position than AMD. Investors may note that Broadcom's stock is more expensive than AMD's, but this premium is justified.

Caption: AVGO vs AMD Forward Price-to-Sales Ratio Comparison, Source YCharts

Analysts expect Broadcom's growth to be significantly faster than AMD's, and the valuation gap between the two is not that large. Especially after the pullback following the earnings report, Broadcom is more worthy of a buy.

Domande pertinenti

QAccording to the article, what are the main differences between AMD's and Broadcom's strategies in the AI chip market?

AAMD is taking a generalist approach, competing directly with Nvidia in the market for general-purpose AI GPUs. In contrast, Broadcom follows a differentiated, custom chip (XPU) strategy, designing chips tailored to the specific AI workloads of individual clients like Anthropic, Google, Meta, and OpenAI.

QWhat reason does the analyst give for Broadcom's stock being more expensive (having a valuation premium) compared to AMD's?

AThe analyst argues that Broadcom's premium valuation is justified because it holds a superior competitive position with a roster of top-tier AI clients and is projected to grow significantly faster than AMD, as it progresses toward its long-term AI revenue target of $100 billion annually by fiscal 2027.

QWhat was the market reaction and the CEO's response following Broadcom's latest quarterly earnings report?

AFollowing its Q2 earnings report, Broadcom's stock fell sharply due to a Q3 AI revenue forecast that fell short of expectations. However, CEO Hock Tan reaffirmed the company's long-term target of achieving $100 billion in annual AI chip sales by fiscal 2027.

QWhat is identified as a key competitive barrier that makes it difficult for AMD to challenge Nvidia's dominance?

AThe article identifies Nvidia's CUDA software ecosystem as a key competitive barrier or 'moat.' Major clients like Meta are deeply entrenched in this ecosystem, making it very difficult for competitors like AMD to overcome through hardware specifications alone.

QWhy might Broadcom's custom chip (XPU) strategy become even more advantageous in the future, according to the article?

AThe article suggests that as the focus of computing demand shifts from AI training to inference, efficiency becomes more critical. Broadcom's custom chips, which are optimized for specific client workloads, offer efficiency advantages that will likely become even more valuable in this evolving market landscape.

Letture associate

Xpeng and NIO Compete on Computing Power, Li Auto Shifts Architecture

On June 15, 2026, Li Auto unveiled details of its self-developed chip, Mahe M100, for its new L9 Livis model. CTO Xie Yan stated the goal was not just a faster chip, but a fundamentally different one, targeting the chip architecture itself. While competitors like NIO, Xpeng, and Huawei highlight TOPS (computing power) figures for their self-developed chips, Li Auto’s Mahe M100 focuses on redesigning the underlying architecture. It employs a "dynamic data flow architecture" to address memory bandwidth bottlenecks in large model inference, claiming up to 3x the effective computing power of Nvidia's Thor U for its specific workloads and a 40% reduction in latency. The chip's design was peer-reviewed and accepted at ISCA 2026. However, this performance is highly optimized for Li Auto's own VLA2.1 algorithm, meaning it may not generalize as well to other tasks. Li Auto aims to achieve full-stack in-house development with Mahe M100, covering chip, compiler, OS, AI algorithms, and domain controller—a level of vertical integration few competitors match. Beyond the chip, CEO Li Xiang introduced a new strategic narrative: the "embodied intelligent vehicle," defined as an integration of an EV, a professional driver, an AI computer, and a life assistant. This shifts competition from features like large screens to systemic AI capabilities. A key commitment was that Li Auto's Mahe VLA autonomous driving model will match Tesla's FSD V14 by Q4 2026, with specific OTA milestones set for July, September, and December. Financially, Li Auto faces pressure with declining revenue and vehicle gross margins since Q4 2025, while maintaining high R&D investment (approx. ¥12B in 2026, 50% AI-related). Its 2026 sales target is 550,000 vehicles, up from 406,000 in 2025. The new L9 Livis garnered over 10,000 pre-orders in two weeks. The effectiveness of these strategic moves—new products, OTAs, and the novel chip architecture—will begin to show in Q3 2026 financial results, with the year-end FSD V14 benchmark being the ultimate test.

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