Arista Networks: Ethernet AI Networking Opportunity

GPU sales are surging at the moment, primarily from Big Tech’s $200 billion in capex for AI infrastructure services. Critical data center components, including networking, are required for GPU systems. There is a well-quoted discussion from Dell executives earlier this year, that by the end of the systems lifecycle, $2 to $3 will be spent on networking and storage for every $1 spent on GPUs. Granted, the effects of this 2-X market demand will be spread across many more players compared to GPUs. Yet, there is ample evidence that networking is sparking a remarkable growth trajectory of its own. For example, Nvidia’s InfiniBand has seen triple digit growth, Cisco has provided strong AI commentary, and Arista Networks’ view is that networking is mission-critical to improve GPU utilization.

Arista Networking is positioning itself as a pure-play in AI-driven networking, and management sees tailwinds to growth not only via Ethernet establishing itself as the go-to choice in networking, especially for AI training, but also stemming from the broader market opportunity arising from the massive shipment volumes of Nvidia’s GPUs.

Why Data Center Spend Is Accelerating

The current AI landscape is spearheaded by Big Tech. Microsoft and Amazon are touting multi-billion-dollar cloud revenue run rates from AI, Google sees a clear path to monetizing AI features, and Meta is aggressively investing in AI with some initial evidence it’s boosting average revenue per user (ARPU). What’s unfolding is an AI ‘arms race’, in that Big Tech, and a handful of startups including OpenAI, Mistral, Anthropic, and others, are competing to develop, deploy and commercialize the next cutting-edge AI model. This race also spreads over to who can develop the best AI assistants/Copilots, increase adoption of GenAI tools, and accelerate revenue growth in the cloud.

Nvidia CEO Jensen Huang explained exactly why this race is rapidly unfolding, and why Big Tech’s AI expenditures are increasing not only this year, but likely for the next few years: “time is really, really valuable to them. Let me give you an example of time being really valuable, why this idea of standing up a data center instantaneously is so valuable and getting this thing called time to train is so valuable. The reason for that is because the next company who reaches the next major plateau gets to announce a groundbreaking AI. And the second one after that gets to announce something that's 0.3% better. And so the question is, do you want to be repeatedly the company delivering groundbreaking AI or the company delivering 0.3% better? And that's the reason why this race, as in all technology races, the race is so important. And you're seeing this race across multiple companies because this is so vital to have technology leadership, for companies to trust the leadership and want to build on your platform and know that the platform that they're building on is going to get better and better.”

The conclusion is that Big Tech firms are snapping up Nvidia’s GPUs as fast as they reach the market, and this demand spills over into AI servers and networking components, as both are crucial for AI systems.

Networking Becoming Indispensable

Big Tech is deploying thousands to (soon) millions of GPUs and in-house AI accelerators, and networking is a mission-critical piece. Switches are crucial for communication inside the GPU clusters, allowing quick, efficient communication and transfer of data between each node, which is essential for parallel processing, and thus overall job completion time when it comes to training large-scale AI models and completing larger workloads.

A cohesive networking layer with high-quality switching technology can lower power consumption needs significantly and improve performance job completion times. As a result, the industry is going all-in on Ethernet, Nvidia included, in part due to its compatibility, cost and performance advantages, and security.

According to Arista, Ethernet has advantages over Nvidia’s InfiniBand: “AI workloads are placing greater demand on Ethernet, as they are both data and compute-intensive across thousands of processes today. Basically, AI at scale needs Ethernet at scale. AI workloads cannot tolerate the delays in the network, because the job can only be completed after all flows are successfully delivered to the GPU clusters. All it takes is one culprit of worst-case link to throttle an entire AI workload.”

Broadcom’s management seconded this, explaining that as companies scale GPU clusters, they are “going to have to use the best networking technology. And we believe that the best networking technology is Ethernet.” Broadcom’s Ram Velaga added that whether GPUs are “connected inside a data center or across data centers, you cannot get around the fact that you have to connect multiple GPUs. Once you accept the fact that it is a distributed computing problem and you need a network, then I would make a very strong case for you that the best network in the world, over multiple generations, over and again, has been Ethernet.”

Velaga used Meta as an example as to why networking (and Ethernet) is so important: when Meta is running “large workloads, anywhere between 18% to 57% of the time, the traffic is just sitting in the network. That means during this period of time, the GPUs are actually sitting idle. Now think about it. If on an average somebody is charging somebody between $20,000 to $30,000 per GPU and you've got 100,000 GPUs, you're talking about a $2 billion to $3 billion infrastructure. And if $2 billion to $3 billion infrastructure is sitting idle for 18% to 57% of the time, that's a lot of money, right?”

By creating more efficient lines of communication between GPUs, Ethernet can help accelerate job completion times, and in turn, allow more jobs to be completed on the clusters. Velaga touched upon the performance advantages of Ethernet versus Nvidia’s InfiniBand, noting that Meta tested both on a 24,000 GPU cluster and found that Ethernet provides up to 10% better performance at half the cost, which, when translated over to overall infrastructure costs, could equal hundreds of millions to billions saved.

Nvidia is also prioritizing Ethernet with its new Spectrum-X solution, despite seeing strong triple-digit networking revenue growth (accelerating from 94% YoY to 242% YoY in 4 quarters to over $3 billion in quarterly revenue) driven by InfiniBand. CEO Jensen Huang said Nvidia is “all-in on Ethernet” with an “exciting road map coming.” He added that “Spectrum-X is ramping in volume with multiple customers, including a massive 100,000 GPU cluster. Spectrum-X opens a brand-new market to NVIDIA networking and enables Ethernet only data centers to accommodate large-scale AI. We expect Spectrum-X to jump to a multibillion-dollar product line within a year.”

For more information on how Ethernet compares to InfiniBand, reference our analysis: “Broadcom: Networking/ASICs Giant and The Second Largest by AI Revenue” where we go through a side-by-side comparison including why Big Tech is pushing for Ethernet over Nvidia’s in-house InfiniBand.Broadcom: Networking/ASICs Giant and The Second Largest by AI Revenue” where we go through a side-by-side comparison including why Big Tech is pushing for Ethernet over Nvidia’s in-house InfiniBand.

Arista Confident in Ethernet Opportunity

Arista echoed much of Broadcom’s comments on Ethernet’s performance advantages versus InfiniBand, reiterating that Ethernet is “proving to offer at least 10% improvement of job completion performance across all packet sizes versus InfiniBand.”

Arista added that they are “witnessing an inflection of AI networking and expect this to continue throughout the year and decade” as Ethernet emerges as “a critical infrastructure across both front-end and back-end AI data centers.”

Per Arista’s Q1 call, we are “progressing well in four major AI Ethernet clusters that we won versus InfiniBand recently,” and in the four clusters, they are “migrating from trials to pilots, connecting thousands of GPUs this year, and we expect production in the range of 10K to 100K GPUs in 2025.”

Arista’s management reiterated the company will reach an AI target of $750 million in 2025. Barclays believes Arista “can top its guidance of $750M in AI-related back-end revenue for 2025,” commanding 18% market share in data center switching (versus 27% share for Nvidia and 22% for Cisco).

Arista also has a few core risks, particularly in that revenue is heavily concentrated in two major customers, Microsoft and Meta, accounting for 38% of company-wide revenue ($2.2 billion of Arista’s $5.8 billion in revenue in 2023). While we are seeing both companies spending quite aggressively in AI this year and next, revisions to capex plans intra-year (much like how we saw Meta increase its full year capex guide last quarter) can move Arista’s stock price.

Microsoft and Meta accounted for 39% of Arista’s revenue in 2023, down slightly from 42% in 2022 but up significantly from less than 25% in 2021. In dollar terms, the two are both billion-dollar customers, with revenue from Microsoft increasing more than 50% in 2023 and nearly 59% in 2022.

Both Microsoft and Meta increased 2024’s capex plans, with Microsoft’s Q1 capex rising 80% YoY to $14 billion, and full fiscal year capex up 50% YoY to $50 billion. Microsoft is reportedly seeking to triple its GPU supply this year to 1.8 million GPUs to support AI demand on Azure, and demand for networking components should rise hand in hand.

Meta boosted its full year capex range to $35-40 billion, pointing to 33% YoY growth and $4 billion more than previously anticipated, to build out AI infrastructure and support its internal AI roadmap. Meta’s Q1 capex was only $6.7 billion, implying that the bulk of this spend will hit in the second half of the year, possibly accelerating at a ~20% QoQ rate and exiting 2024 above the $11 billion range – hinting that Meta’s contributions to Arista’s revenue growth may not be felt in full force until the back half of 2024.

While the capex growth is positive, competition in the networking space is high, from Broadcom to Nvidia to Cisco to others. Cisco noted that it has been seeing strong momentum in Ethernet AI fabric deployment at three of the top four hyperscalers, possibly alongside Arista’s solutions, while Nvidia has recently released its Spectrum-X Ethernet solution which it expects to become a multibillion-dollar product line with a year. According to Nvidia, Spectrum-X delivers 1.6X better networking performance than traditional Ethernet.

Our previous Broadcom analysis points toward the Ethernet networking giant being second in AI revenue, primarily from AI networking revenue. Forward-looking, Broadcom is expected to end the year with $2.75 billion per quarter in AI revenue for $11B per year. Compare this to Nvidia’s networking revenue at $3.2 billion.

InfiniBand increases dependency on Nvidia, requires a new networking stack, and lags Ethernet on raw bandwidth. Improvements in Ethernet systems are expected to offer better load balancing and congestion control to help close the gap with InfiniBand’s low latency. Broadcom’s Jericho3-AI switch platform is the company’s AI fabric that competes with InfiniBand on AI training completion times, and it allows for more than 32,000 GPUS to be linked for a massive AI training system.

Regarding Arista, the company has partnered to offer a holistic solution, where a remote Arista-based AI agent will help customers optimize and manage their AI clusters with a single control point; however, investors should expect competition in the market to remain fierce as hyperscalers continue to build out data center infrastructure.

Financials: Margins Remain Strong Despite Decelerating Growth

Turning to fiscal Q1’s earnings — Arista delivered a solid report, with revenue ahead of expectations as margins remained strong. However, headline revenue growth has decelerated rather quickly as Arista faced difficult comps in Q1. Despite the deceleration, the bottom line remains strong and in fact is strengthening.

In terms of AI revenue, management did not provide a figure for 2024, but its $750 million target for 2025 would represent close to 10% of total revenue, with consensus for FY2025 at $7.82 billion.

Revenue and EPS:

Arista reported revenue of $1.57 billion in Q1, representing YoY growth of 16.3% and beating expectations by nearly $24 million. This is down from 54% growth in the year-ago quarter. Growth is expected to decelerate more than 4 percentage points on a sequential basis in Q2.
GAAP EPS of $1.99 represented YoY growth of 44.2%, beating estimates by $0.40.
For Q2, Arista guided revenue between $1.62 billion and $1.65 billion, representing YoY growth of 12.1% at midpoint, a fifth consecutive quarter of decelerating revenue growth. However, Q2 is expected to mark the bottom, with analysts expecting growth to reaccelerate to the 14%+ range by Q4.

Margins:

Gross margin was 63.7% in Q1, down 120 bp QoQ from a six-year high in Q4 at 64.9%. Gross margin has been relatively stable in the 63% to 64% range aside from a dip to the 60% range in the first half of 2023.
Operating margin reached a record high at 42.0% in Q1, and represented a 50 bp QoQ and 610 bp YoY expansion. Operating margin has expanded steadily since 2021, increasing nearly 10 percentage points from the low 30% level.

Net margin was 40.6%, up 80 bp QoQ and 830 bp YoY. Arista’s bottom line strength should not be overlooked, especially as leverage improves down the line even with decelerating revenue growth. In the market’s top AI stocks at the moment, Arista has one of the strongest bottom lines outside of Nvidia.

Cash and Debt:

Arista reported cash and equivalents of $5.45 billion, and has zero debt.
Cash flow margins are strong — operating cash flow increased over 37% YoY to $514 million, for a 32.7% margin. Free cash flow also increased 37% YoY to $504 million, for a 32% margin.

How Arista Networks Ranks on AI Revenue:

Here’s a quick glance on the rankings for AI networking revenue, with Arista near the bottom of the list. Nvidia and Broadcom lead the sector, with Nvidia recently surpassing a $13 billion annual run rate in networking.

Nvidia is in first with $3.2 billion in networking revenue in fiscal Q1, after recently surpassing a $13 billion annual run rate in Q4. Nvidia is expecting its new Spectrum-X product to reach a multi-billion dollar run rate “within a year.”
Broadcom is in second place with AI revenue of $3.1 billion in fiscal Q2, projecting an annual run rate of more than $11 billion, or more than $2.75 billion per quarter. Based on management’s commentary, networking likely contributed upwards of $1 billion in the quarter, and could exit the year in the mid-$4 billion range.
Marvell reported approximately $500 million in AI revenue in the most recent quarter, with management eyeing a “a floor of $1.5 billion for AI revenue” for this fiscal year, with two-thirds coming from electro-optics and one-third from ASICs.
Juniper Networks reported $321.2 million in the AI enterprise segment, or 23.5% of revenue. Recently, it was announced that Juniper is being acquired by HPE.
Arista has not broken out AI revenue on a quarterly basis yet, but is targeting $750 million in AI revenue in 2025, which is equivalent to ~10% of revenue for that year.

Valuation:

Arista’s top line valuation has surpassed historical peaks. Bottom line strength and improved operating leverage are driving increased earnings power exiting 2024 with a bottom line valuation in line historically.

Arista currently trades at 19.4x sales and 17.3x forward sales, both above historical highs – in late 2021, Arista peaked at just under 17x sales, the same level where it pulled back from in early May following its post-earnings rally. Buying in the 8x sales range offers a higher probability for upside, although notably, AI stocks have not offered low entries over the past year.

On the bottom line, Arista trades slightly below 52x earnings and nearly 47x forward earnings, which on the surface is expensive, and above its 5-year average of 34x. Arista peaked at 60x earnings at its 17x sales peak multiple in late 2021, providing a tiny bit of breathing room for the bottom-line valuation on improved earnings power later this year and through next; however, downside risk is more prevalent as both the top and bottom-line valuations become stretched.

There are currently two counts that I see playing out in this final push higher. Both counts have us in the final swing higher of the larger 3rd wave, they only differ on how high this swing can go before we see a larger pullback:

Technical Analysis

By Knox Ridley

Green – If we can breakout over $390 and hold this level, then the odds favor this path higher. This would target the $440 – $480 region directly. The final target should be between $490 – $520 before we see the larger 4th wave pullback.

Red – If we fail to breakout over $390, and instead see a breakdown below $335. This would signal that we are in the 4th wave drop, which I generally have targets between $260 – $200. If this plays out, as long as we hold $195, this would be a decent buying opportunity for the final 5th wave swing higher.

Conclusion

InfiniBand has been reporting up to 500% growth and more recently 300% growth, yet for the first time since the AI surge, Nvidia reported that networking declined sequentially this past quarter.

Despite Nvidia’s GPU moat being fully intact, its networking lead is in question. Gartner recently reported that by 2028, 80% of hyperscalers will “opportunistically” prefer Ethernet over proprietary technologies. According to Broadcom, this shift is happening quickly with management predicting that as soon as next year “all mega-scale GPU deployments will be on Ethernet.”

Arista Networks is a stock to watch in this space, primarily for its defensibility on the bottom line. The company sees $750 million in back-end AI revenue in 2025 stemming from growth among hyperscalers. Heavy revenue concentration in Meta and Microsoft is a core risk to watch, yet capex spend is accelerating for the time being, providing growth tailwinds for the networking industry as a whole. Next week, we will revisit another Ethernet networking play with more revenue and a stronger growth story for 2025, despite being weaker on the bottom line.

Damien Robbins, Equity Analyst at the I/O Fund, contributed to this article.

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