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Founded in 2004, Arista became a leader in cloud networking at a time when bigger rivals were slow to seize that opportunity. Some investors have worried that the Santa Clara, Calif.–based company has been too dependent on a handful of huge clients (including Meta and Microsoft); Arista’s recent moves to diversify its client base and expand into data warehousing have eased those concerns somewhat. Analysts expect the company to generate $5.9 billion in revenue this year, up 34% from 2022. Arista has been led since 2008 by Jayshree Ullal, one of three female CEOs on this year’s Future 50.

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Arista is headquartered in Santa Clara, California, and known for its cloud networking platforms, including its Extensible Operating System (EOS) and CloudVision software, along with high-performance switches and routing products. It serves data center, campus, and routing environments, with particular strength in large cloud and AI infrastructure deployments.  Arista’s customer base includes some of the world’s largest cloud operators and enterprise technology users.

Q2 2026

Q1 2026

Arista Networks (ANET): Company Profile, Stock Price, News, Rankings

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Arista Networks

arista networks

Welcome to the first quarter 2026 Arista Networks financial results earnings conference call. During the call, all participants will be in a listen-only mode. After the presentation, we will conduct a question and answer session. Instructions will be provided at that time. If you need to reach an operator at any time during the conference, please press the star key followed by zero. As a reminder, this conference is being recorded and will be available for replay from the Investor Relations section on the Arista website following this call. Mr. Rudolph Araujo, Arista's Head of Investor Advocacy, you may begin.

Thank you, Regina. Good afternoon, everyone, and thank you for joining us. With me on today's call are Jayshree Ullal, Arista Networks Chairperson and Chief Executive Officer, and Chantelle Breithaupt, Arista's Chief Financial Officer. This afternoon, Arista Networks issued a press release announcing its fiscal first quarter results for the period ending March 31st, 2026. If you want a copy of this release, you can find it on our website.

During the course of this conference call, Arista Networks management will make forward-looking statements, including those relating to our financial outlook for the second quarter of the 2026 fiscal year, longer term business model and financial outlooks for 2026 and beyond, our total addressable market and strategy for addressing these market opportunities, including AI, inventory management, lead times, and product innovation, which are subject to the risks and uncertainties that we discuss in detail in our documents filed with the SEC, specifically in our most recent Form 10-Q and Form 10-K, and which could cause actual results to differ materially from those anticipated by these statements. These forward-looking statements apply as of today and you should not rely on them as representing our views in the future. We undertake no obligation to update these statements after this call.

This analysis of our Q1 results and our guidance for Q2 2026 is based on non-GAAP and excludes stock-based compensation expense, intangible asset amortization, gains, losses on strategic investments, and income tax effect of these non-GAAP exclusions, including the recognition of direct access tax benefits associated with stock-based awards. A full reconciliation of our selected GAAP to non-GAAP results is provided in our earnings release. With that, I would turn the call over to Jayshree.

Thank you, Rudy, and welcome everyone to our first quarter 2026 earnings call. Arista has experienced significant velocity in all our sectors in Q1 and are now commanding the number one market share in high-speed switching in the greater than 10 Gb Ethernet category. With that, we have overtaken many incumbent vendors according to major market analysts for 2025. Our cloud and AI networking strategy for diverse AI accelerators continues to gain traction. Unlike typical workloads, AI workflow patterns can be long-lived elephant flows or short-lived and simply not predictable. This implies careful attention to performance, where a flow can cause burstiness for a long duration of milliseconds. The intensity of a flow can determine the line rate throughput. The shifting traffic patterns to massive flows synchronized to all-to-all or all reduce or bursts of collective communication are all important for AI training and inference applications.

I would like to take a moment to review our three AI fabric use cases. In scale-up mode, we have familiar technologies such as NVLink and PCIe that have enabled vertical scaling of single compute nodes or racks. The advent of ESUN, Ethernet for Scale-Up Networking specifications, allows for increasing or decreasing computing power in a flexible manner with Ethernet to automatically adapt to workload demands. Scale-up will be a new entry for Arista in 2027 and beyond, where we will be working closely with our customers to build AI racks with very fast interconnects for co-packaged copper, CPC, or open co-packaged optics, CPO, as well as supporting collectives and memory acceleration. Scale-out or horizontal scaling involves adding more machines to a leaf-spine fabric, moving workloads across multiple servers or nodes, or even connecting other elements like storage or CPUs.

As you scale up or out with massive datasets, bottlenecks can be resolved with collectives and protocol acceleration at L2, L3, cluster load balancing all at wire rate. The system must deliver consistent performance without degradation as more nodes participate. Arista is a shining example here with greater than 100 cumulative customers to date in 800 GB Ethernet deployments, and we expect the addition of 1.6 TB in 2027 at production scale. Scale-across drives across the cloud and AI as the AI accelerators in a location may need to be distributed to achieve the appropriate bandwidth capacity with the optimal power. As workloads become more complex and more distributed, the bisectional bandwidth must scale smoothly to avoid bottlenecks and preserve performance.

This demands sophisticated traffic engineering, deep routing, encryption properties, and integrated optics based on Arista EOS stacks and using Arista's flagship 7800R3 or 7800R4 series. The 7800 has established itself in this category as the premier scale across choice. You can see with Arista's accelerated networking strategy and these three types of AI fabrics, these are critical to deployment of diverse accelerators and frontier models. Traditional static network topologies with hotspot jitter that slows down job completion time or increases time to first token for inference are all not the way to go. Arista's EtherLink portfolio addresses both the synchronous flows for massive training and the low latency for concurrent swarms of real-time inference in this era of trillions of tokens, terabits of performance, and terawatts of power.

In 2024, you may recall we discussed four Ethernet-based AI training deployments, and of course, since then we've expanded and exploded to countless others. This fourth customer from the group has officially moved from InfiniBand to Ethernet at production scale over the last two years. The high-speed Ethernet AI leaf-spine with flexible air or liquid-cooled infrastructure overcomes the physical constraints of power and space for AI workloads. It results in a low latency distributed AI supercomputer fabric across global regions. What is clear to me and us is our networking prowess with data, control and management, and multiplanar orchestration is not only central to our AI switching performance, but also important for high-speed optics transmission. At the recent Optical Fiber Communication Conference, Arista unveiled its extended pluggable optics, XPO form factor, designed specifically for optics innovations at high speed.

Now endorsed by greater than 100 vendors, salient features include record-breaking throughput, delivering 12.8 TB per pluggable module. Unprecedented rack density achieving 204.8 TB per OCP rack unit. Integrated cold plate capable of cooling up to 400 W power per module. The universality and flexibility across a range of pluggable optics copper, as well as linear half-retimed or retimed interfaces. A special kudos to Andy Bechtolsheim, Arista's Chief Architect, for driving from OSFP 10 years ago to this next generation XPO, bringing structural improvements in power, footprint, and cost reductions. Our enterprise business experienced strong results in Q1 2026, both in data center and campus. Our VeloCloud acquisition is also integrating well into our branch and campus strategy, bringing more distributed enterprise use cases and a new channel motion with managed service providers, MSPs.

To share some recent wins, let us hear now from Todd Nightingale and Ken Duda, our co-presidents, to delineate our Arista 2.0 centers of data strategy. Over to you.

Thanks, Jayshree. Arista is diversifying its business with new customer acquisitions covering a broad set of use cases, all unified by Arista's EOS stack and its ability to modernize enterprise infrastructure operating models. Our first highlighted win is a NeoCloud AI network. The customer was constrained by an incumbent white box architecture that simply could not keep pace with the massive scale-out requirements of AI. Arista was selected as a commercially proven and reliable scale-out architecture with unmatched stability of EOS and the ability to connect AMD MI-series XPUs. Arista's AI leaf and spine Etherlink products were deployed at 800 Gb to provide the incredible performance modern AI networks require. The AI fabric was tuned using Arista's cluster load balancing to scale out to thousands of XPUs, minimizing hotspots and congestion.

On the software side, the customer leveraged AVD, Arista's Validated Design framework, to automate network provisioning, which both reduces the total cost of ownership, but also provides an easy path to reliable network deployment at scale, where without AVD automation, a small mistake can cost precious days of debugging time. This was a strategic NeoCloud win with large potential for upside growth in an area where we are seeing enormous opportunity and velocity in both NeoCloud and Sovereign cloud customers. Our next win is in the service provider sector with a leading regional fiber to the home provider serving hundreds of thousands of subscribers. As subscriber bandwidth demands have surged, this customer realized their legacy routing architecture was too rigid, too brittle, and too costly to scale. They needed a solution which would modernize their next generation backbone and internet peering edge.

Arista won this upgrade by proving an automation-first approach with a modern operating model driving operational savings and increased subscriber reliability. On the hardware side, we deployed popular 7280 routing platforms using EOS's FlexRoute capabilities, which unlock deep buffering, a rich control plane software stack, and full internet route scale. On the software side, Arista's AVD framework again automates router provisioning to reduce the time it takes to turn up services while also reducing errors. Here we saw great results from our technology partnership with Palo Alto Networks, ensuring the routing edge integrated securely and seamlessly with our overarching security architecture. Here, Arista's core value proposition of lower operating costs and greater reliability drove a competitive win. Now I'll hand it off to Todd.

Thanks, Ken. Our third win is in the insurance services sector. Following a year of strategic collaboration, the customer wanted to modernize their infrastructure with a streamlined, automated foundation capable of delivering granular real-time insights to secure and monitor critical applications. Here, observability was truly the key. Arista secured this comprehensive win after executing a flawless proof of concept, proving our architecture significantly exceeded operational standards. To achieve deep network observability, the customer deployed our R3 series for filter and delivery roles on our monitoring fabric, DMF. Additionally, they deployed campus switches to radically simplify out-of-band management. Leveraging our rich telemetry capabilities of EOS, the customer unlocked advanced features like VXLAN header stripping and transitioned to a fully automated declarative operational model. Our final win is within the manufacturing sector, where we're seeing amazing momentum.

Here we have a customer operating more than 100 factory sites globally, servicing consumer, healthcare, aerospace, defense, and AI infrastructure customers. This was a true mission-critical use case, and their legacy campus network had become the bottleneck for achieving real 24/7 production. Shifting traffic patterns, manual provisioning, and importantly, a lack of visibility and forensics into microbursts and drops were keeping them from achieving their goals. Arista won an extensive bake-off against two established vendors, both of whom proposed campus design that could not match what Arista delivered. A universal leaf-spine campus based on open standards running a single EOS binary across campus, data center, and WAN. The cognitive campus solution leveraged a 100 Gb campus spine, high-powered PoE leaves, and Arista Wi-Fi 7. CloudVision drove provisioning, configuration, and lifecycle end-to-end with consistent tooling across the network infrastructure.

Here it really was Arista's modern operating model that drove differentiation in the engagement. Hit list production upgrades, latency analyzer for microburst visibility, and true packet drop forensics. The teams were able to significantly reduce production impacting maintenance windows and expose events that had previously caused line interruption. In all four of these examples, Arista's support team stood out to customers for its best-in-class service, well known for troubleshooting issues with customers long after Arista gear is no longer suspected to be at fault. Arista's modern operating model also played a key role, especially the AVD tooling that Ken mentioned for architecture, validation, and deployment. We're excited about the momentum across the entire enterprise business and especially the diversification that it brings to Arista. Thanks, Jayshree.

Thank you, Todd. Thank you, Ken. It was so fantastic to hear of happy customer outcomes. We had another fitting example of that at our Innovate 2026 event here in the headquarter facility held in March. The energy and enthusiasm of our greater than 250 customers who attended was truly infectious and inspiring. I want to especially give a shout-out to Ashwin Kohli and Dhivya Wagner's teams, who have already improved our outstanding net promoter score from 87 to 89 ratings, translating to a 94% customer approval. This really exemplifies the lowest security vulnerabilities in the tech industry. It enhances our ability to better cope with the many risks that AI is creating. As I look ahead at the year, our Arista 2.0 momentum continues to march on and resonate. Our demand is actually the best I have ever seen in my Arista tenure.

The supply, however, is a slightly different and opposite tale. We are experiencing industry-wide shortages across the board, be it wafers, silicon chips, CPUs, optics, and of course, memory that I referred to last quarter, coupled with elevated costs to procure these. Clearly, our demand is outstripping our supply this year. While we hope the supply chain will ease in the next year or two, the Arista operations team has been diligently engaging with our vendors in strengthening supply agreements and engaging in multi-year purchase commitments. We anticipate gross margin pressure due to mix and trade-offs we are making to pay more to assure supply continuity to our customers. Nevertheless, it gives us confidence to increase our forecasted growth slightly to 27.7%, aiming now for $11.5 billion for 2026.

We also increased our AI target now to $3.5 billion this year, thereby more than doubling our AI sales annually. With that good news, over to you, Chantelle, for the financial details.

Thank you, Jayshree. I continue to be impressed by our company's ability to deliver such a breadth and depth of networking innovation. It is a core tenet that underpins our strong financial return to shareholders. Q1 to detail our most recent financial outcomes. To start off, total revenues in Q1 were $2.71 billion, up 35.1% year-over-year and above our guidance of $2.6 billion. Growth was seen across the customer sectors, led by our AI and specialty providers customers within the quarter. International revenues for the quarter came in at $418.9 million or 15.5% of total revenue, down from 21.2% last quarter. This quarter-over-quarter decrease was primarily influenced by Americas-based sales to our large global customers.

The overall gross margin in Q1 was 62.4% within the guidance range of 62%-63% and down from 63.4% in the prior quarter. This quarter-over-quarter decrease is due to the lower mix of sales to our enterprise customers in the quarter. Operating expenses for the quarter were $396.8 million or 14.6% of revenue, down slightly from last quarter at $397.1 million. Our R&D spending came in strong at $271.5 million or 10% of revenue. Despite a slight sequential decrease due to the timing of new product introduction costs, Arista continues to demonstrate its commitment and focus on networking innovation.

Sales and marketing expense was $103.5 million or 3.8% of revenue, down from 4% last quarter, representative of the highly efficient Arista go-to-market methodology. Our G&A costs came in at $21.8 million or 0.8% of revenue, down from $26.3 million last quarter, reflecting our strong base cost productivity within a pure play networking business model. Our operating income for the quarter was $1.29 billion or 47.8% of revenue. Let me pause here to thank the greater Arista team for all of their efforts and resulting excellent execution in a dynamic environment. Other income and expense for the quarter was a favorable $110.8 million, and our effective tax rate was 21.1%.

Overall, this resulted in net income for the quarter of $1.11 billion or 40.9% of revenue. Our diluted share count was 1.27 billion shares, resulting in a diluted earnings per share for the quarter of $0.87, up 31.8% from the prior year. Now turning to the balance sheet. Cash, cash equivalents, and marketable securities ended the quarter at approximately $12.35 billion. In the quarter, we did not repurchase our common stock. Of the $1.5 billion repurchase program approved in May 2025, $817.9 million remain available for repurchase in future quarters. The actual timing and amount of future repurchases will be dependent on market and business conditions, stock price, and other factors. Now turning to operating cash performance for the quarter.

We generated approximately $1.69 billion of cash from operations in the period, the strongest in the history of Arista. This was driven by a robust earnings performance coupled with an increase in deferred revenue. DSOs came in at 64 days, down from 70 days in Q4 due to the linearity of shipments within the quarter. Our inventory turns improved slightly, landing at 1.7 versus 1.5 in the prior quarter. We ended the quarter with $2.38 billion in inventory, up from $2.25 billion last quarter. This marginal increase is a calculated investment in the mix of raw materials to fulfill our growing demand. Our purchase commitments at the end of the quarter were $8.9 billion, up from $6.8 billion at the end of Q4.

As mentioned in prior quarters, this expected activity mostly represents purchases for chips related to new products and AI deployments. We will continue to have some variability in future quarters as a reflection of the combination of demand for our new products, component variability, and the lead times from our key suppliers. This could also result in quarters of elevated inventory balances ahead of the deployments. Our total deferred revenue balance was $6.2 billion, up from $5.37 billion in the prior quarter. The majority of the deferred revenue balance is product related. Our product deferred revenue increased approximately $643 million versus last quarter. We remain in a period of ramping our new products, winning new customers, and expanding new use cases, including AI.

These trends have resulted in increased customer specific acceptance clauses and an increase in the volatility of our product deferred revenue balances. As mentioned in prior quarters, the deferred balance can move significantly on a quarterly basis independent of underlying business drivers. Accounts payable days were 54 days, down from 66 days in Q4, reflecting the timing of inventory receipts and payments. Capital expenditures for the quarter were $54.5 million. We continue the construction work to build expanded facilities in Santa Clara. In Q1, we incurred approximately $40 million in CapEx related to this program and estimate it will reach $180 million in 2026. These Q1 results have provided a strong start to our fiscal year 2026.

As Jayshree mentioned, we are now pleased to raise our 2026 fiscal year outlook to 27.7% revenue growth, delivering approximately $11.5 billion. We maintain our 2026 campus revenue goal of $1.25 billion and raise our AI fabrics goal from $3.25 billion-$3.5 billion. I would like to take this opportunity to remind the audience that the timing and outcome of customer projects with acceptance terms can create quarterly and sequential dynamics that do not follow prior year trends. For gross margin, we reiterate the range for the fiscal year of 62%-64%, inclusive of mix and anticipated supply chain cost increases for memory and silicon. Given this challenging supply backdrop, I am proud of our sourcing team's execution, which strongly contributes to the gross margin outlook holding in our guidance range.

We feel confident that we can source the necessary supply to meet our customers' needs. Our operating margin outlook remains at approximately 46% for the fiscal year, with the tax rate expected at 21.5%. On the cash front, we will continue to work to optimize our working capital investments with some expected variability in inventory and cash flow from operations due to the timing of component receipts on purchase commitments. More specifically now, our guidance for the second quarter is as follows. Now with the added quarterly metric of diluted earnings per share. Revenues of approximately $2.8 billion. Gross margin between 62% and 63%. Operating margin between 46% and 47%. Diluted earnings per share of approximately $0.88 with approximately 1.27 billion diluted shares. Our effective tax rate is expected to be approximately 21.5%.

In closing, we are optimistic about the fiscal year ahead. The industry has many times demonstrated the pattern of landing on Ethernet as the winning technology, and that is where Arista shines best. We appreciate our customers' choice of working with us to achieve their business outcomes. Now, Rudy, back to you for Q&A.

Thank you, Chantelle. We will now move to the Q&A portion of the Arista earnings call. To allow for greater participation, I'd like to request that everyone please limit themselves to one question. Your line will be placed on mute after your question. Thank you for your understanding. Regina, please take it away.

We will now begin the Q&A portion of the Arista earnings call. To ask a question during this time, simply press star and then the number one on your telephone keypad. If you'd like to withdraw your question, press star and the number one again. Please pick up your handset before asking questions to ensure optimal sound quality. Our first question will come from the line of Simon Leopold with Raymond James. Please go ahead.

Great. Thank you very much for taking the question. I wanted to explore your commentary around the scale across opportunity in particular. I guess what I'm trying to get a better sense of is how much revenue, if any, did that contribute last year?

How material is that to the $3.5 billion forecast you're giving this year, and how should that trend longer term? Thank you.

Sure, Simon. I think last year on scale across, we were just beginning. I think they were small numbers, and majority of the numbers were really scale out. That's sort of our heritage, and that's where we excel. If I were to anticipate how it would be this year, again, scale-up is virtually zero and nonexistent because it really only comes to play after the ESON spec. Consider that more a 27, 28 kind of number. I think the number will be really shared between scale across and scale out. I don't know if I can say it's 50/50 or 70/30 or 60/40, but scale across will definitely contribute at least a third of our AI number.

Our next question will come from the line of George Notter with Wolfe Research. Please go ahead.

Hi, guys. Thanks very much. Maybe just continuing the discussion on scale up. You know, we are starting to see rack design wins. One of your competitors in the ODM space, I think, has got a couple of designs that they've announced at least. I know you're kind of pointing towards ESON as being kind of a key, you know, catalyst in generating business there. But can you talk a little bit about where you are in terms of designs with customers, progress?

Anything you can tell us there would be great. In fact, I think a few quarters ago you said you had five to seven scale-up rack designs that you were at least working on.

I'm just wondering if you can update that. Thanks a lot.

Yeah. That's correct. George, I think there is no doubt in our minds that we will have a number of racks, a number of scale-up use cases in 2027. Maybe some of them will be in early trials, but majority of them are looking at really starting with 160, and 160 chips will really happen in 2027. There may be a few, a handful of them that try some experimental stuff at 800 Gb, but we continue to see at least, you know, five to seven rack opportunities. Some of them are multiple racks with the same customer. We're actively designing with them. There's a huge amount of liquid cooling, you know, designs with very dense cabling options, acceleration of collectives and memory, features we have to work on for low latency.

I definitely feel we're in active engineering phase with Ken and Hugh's teams this year. Unlike the ODMs, I think we're held to a higher bar, and we have to just make sure that this thing is production-worthy and specification adhering to ESUN. I would say today's scale-up is mostly limited to NVLink from Nvidia and maybe some PCIe switching. Majority of the Ethernet scale-up will only really happen in 2027 and 2028.

Our next question will come from the line of Antoine Chkaiban with New Street Research. Please go ahead.

Hi. Thank you very much for taking my question. With the supply outstripping demand, I'm wondering, you know, how much does your current supply allow you to grow this year and next? Is the updated, you know, top-line growth guide of 28% growth a good reflection, of how much supply you've secured for this year? What could that number look like next year, you know, based on how much supply you think you can get as of today?

Antoine, I think the supply chain problem, and Todd maybe you can add to this, is not a one or two quarter phenomena. We now think it's a one or two year phenomena. You know, at first we thought it was memory, now it's all the wafer fabrication facilities. Every chip is challenged, and you can see how Chantelle has leaned in with the purchase commitment for multiple years. While we will continue to improve it, this is a reflection of not just demand, but how much we can ship this year. As we continue to ship this year, we can give you better visibility on next year. I can just tell you, we see multi-year demand, and we are gonna do everything, including hurt our gross margins to supply to that demand this year and next year.

Because we believe that we certainly don't wanna keep GPUs idle and AI infrastructures underutilized because Arista didn't supply the network. Can the number get better this year? I think this reflects our best attempt at a good number. We started out at—Did we start out at 20%, 25% growth? Yeah. We started out at 20%, we're at 25%, now we're at 27.7%. Could we improve to the tail end of the year? We'll see. The amount of decommits we're seeing doesn't feel good. We think a lot of this will continue into next year and keep us constrained for the next couple of years.

Our next question will come from the line of Aaron Rakers with Wells Fargo. Please go ahead.

Yeah. Thanks for taking the question. You know, Jayshree, last quarter you had alluded to kind of engagements with other hyperscale cloud titan customers. I think you also pointed to maybe having one or two new 10% customers this year. I'm curious of, you know, where we stand today. Any updated thoughts on adding one or two new customers at 10% plus? You know, maybe qualitatively just talk about your engagements you're having beyond your two big cloud titans across the hyperscale vertical. Thank you.

Yeah. Absolutely. First of all, our two big ones, we never take them for granted. Microsoft and Meta, they're our all-time favorites. They've been our 10% and greater customers for over a decade, and the partnership could never be stronger, and it continues to get better, both in cloud and in AI. In terms of the new entrants, we still expect at least one, maybe two. Maybe I should caveat this by saying certainly in demand we see one or two. We shall see, Todd, how we do on shipments to see if we can achieve the greater than 10%.

The two of them have very interesting characteristics. They exhibit what I would call the three use cases I just alluded to, scale up, scale out, and scale across, where we really have a fabric notion of creating. You know, so far we've been working with them a lot on the front end, and now we get to complement that on the back end, definitely for scale out and scale across, and maybe even a little bit of scale up, in some of these use cases. The other thing we're seeing with a lot of these use cases is the lack of power in sites, and the ability and demand to distribute and get a more multi-tenant, scale across is very high in these two use cases.

A third common thread we're seeing across all of them, much as we all talk about ODM and white boxes, they deeply appreciate EOS and the features and the reliability and the observability and just the fact that we have a robust, highly scalable layer two, layer three stack commands a lot of superior advantages. I believe the diversity of these cloud titans is largely due to the fact that we have great hardware and software combined. Ken, you want to say a few words on that?

It's just been an incredible journey to live through this and see the level of infrastructure build out we're getting and how well-positioned our hardware and software roadmaps are to address these ever-evolving, more advanced use cases. It's just a blast to get to work on this stuff.

That's always fun when your job is a blast. Ben, I still see one, I think one, maybe two, 10% customers. Todd, hopefully we can ship it.

Our next question will come from the line of Ben Reitzes with Melius Research. Please go ahead.

I, yeah, I wanted to ask around the product, the constraints. Are you able to say what the number was in the quarter and what it's taking away in terms of the $2.8 billion guide? Is it safe to say, you know, things would have been, you know, $100 million or $200 million higher for both? Then if you don't mind, just, if you can touch on why the gross margin should go back up to 63%. You know, what is it that you guys are doing that, what gives us confidence that it can actually expand a tad from here?

Hey, Ben. I think that I don't think the commentary about the demand outstripping the supply is a Q1, Q2. I think we're talking about looking ahead Q3, Q4 into next year. I don't think there's something outside of what we've guided or what we've delivered in the first half. I think in the sense of the margin, the margin's a mix of things, right? I think that all the team members are executing in full force. I think the supply chain's doing everything they can on ensuring that we have the best supply at the best price, we've incorporated that. I think that the mix of customers, the only chance for mix expansion or margin expansion would be due to mix.

I think that's the opportunity as we look to see what we can deliver in the second half, Ben. I think that would be the opportunity.

The teams are also doing everything they can to make sure we control our costs, especially on the manufacturing side. That includes, you know, bringing on secondary providers, qualifying new components, et cetera, to make our supply chain more resilient, and more cost-effective in the long run.

One thing to clarify also on gross margins is we view this as a partnership with our customers. While we did consider and have raised prices a little bit, unlike our competitors, we haven't done two price increases. We haven't done major price increases. The price increases really come into play once our backlog starts to reduce, right? You won't see the impact of that. Our gross margins are a strong factor of cost going up and us still eating a lot of the costs and you know, giving our customers the benefit and promise of the pricing we said we would give to them.

Our next question will come from the line of Michael Ng with Goldman Sachs. Please go ahead.

Hey, good afternoon. Thanks for the question. I was just wondering if you could talk about whether or not Arista's seeing networking attach opportunities for customers that are using TPU or TPU-like architectures. Then, anything you could comment about as it relates to growing NeoCloud traction. Is that something that you think may be a little bit underappreciated by the analyst community? Thank you very much.

Michael, you're absolutely right. I'll take your second question first. It's easy to talk about the titans 'cause the numbers are so ginormous, right? The NeoClouds are a very important sector because they don't always have the staff to do everything they want to do, and they really lean on Arista's design expertise, EOS expertise, you know, network design configurations we can provide them. You know, a family of 22 products we have in AI. Yes, I would agree with you. It's an underappreciated, the NeoCloud was very strong this quarter, if I recall Chantelle, for us in the, in the specialty and cloud providers. What was the other question? You had a 1A, 1B.

Oh, yeah, the TPU. In general, we are seeing diverse accelerators. Last time I spoke about the AMD accelerators. This time I will definitely give a nod to the TPUs, because in particular, scale across use cases, we're seeing multi-tenants connecting to different AI accelerators, including TPUs as well. I think the diversity of accelerators is creating tremendous multi-accelerator opportunity and multi-protocol features that we can provide for them in our network.

Our next question will come from the line of Sean O'Loughlin with TD Cowen. Please go ahead.

Great, thanks. You know, congrats on the results, and thanks for letting me join in on the fun here. Jayshree, wanted to get your thoughts on, you know, we've been talking a lot about agentic AI and the demands that it's placing on maybe some of the more general purpose infrastructure that we've had in the background over the last couple years. You've talked in the past about a two to one pressure, you know, on front-end networking created by back end. First, I guess, is that still the correct way to think about it? Second, you know, as agentic workflows become more common, is there any additional demand, you know, from your perspective having a single-image EOS platform on the front and the back end, or is the front and back end still pretty siloed?

Yeah. Well, first of all, Sean, welcome to your first call. It will be fun. Join the fun. agentic AI, it's kind of a buzzword, but let me sort of break it into how The biggest killer application we see in agentic AI right now is still training. Indeed, it's gonna move to more distributed inference, and we'd also like to see agentic AI move into a lot of enterprise use cases, all of which we are seeing, by the way. I would say large, medium, small. The largest killer agentic AI application is training, the medium is enterprise, and the small is, medium is inference, and the small is obviously enterprise.

In terms of back end versus front end, we are now seeing way more back end activity, particularly with our large AI titans and cloud titans, because there is just so much scale they need to prepare for the billions of parameters and tokens, this is where a lot of so much so that I think the front end, they might come back and refresh, they're almost ignoring right now in favor of the back end. Having said that, though, by virtue of the back end deployments, I don't know if we anymore see a one to one to the front end, we at least see a one to one, the one to one can be wide area, CPU, and storage. Those are probably the three common use cases.

Not all the customers are up and lifting everything and doing all three, although we've had cases where some of them did an upgrade at the front end before they went into the back end, but usually they will have to come back to that because the minute you put that kind of performance pressure and scale on the back end, you almost have to do something in the front end. At the moment, I would say it's more one to one, and at the moment I'd also say the scale across in the back end has become a bigger use case than we imagined this time last year.

The other thing I'd like to mention here is just how good it feels to have the same set of products and the same common operating system management suite and operating model across the front end and back end. This lowers cost for the customer, simplifies their design process to get that leverage, and we're one of the few vendors who can do that.

I think only. Yes, absolutely. Good point, Ken.

Our next question will come from the line of Meta Marshall with Morgan Stanley. Please go ahead.

Great, thanks. appreciate the question. Maybe just a question on XPO monetization or just how it helps you kind of continue to gain share with customers or just mind share with customers by being so front-footed with the technology. Thanks.

Thank you, Meta. I think, as you know, we're not a classic optics vendor, but almost always whenever we're selling our switches, it has to connect to something, and usually it's some form of copper or optics. Andy's innovations with OSFP, I remember this super well, where everybody was saying, "Oh, no, we can just use QSFP," has proven to be, you know, not only a contribution for Arista, but really for the industry wide, and that's still how we see it with XPO as well. You know, while the industry has been talking a lot about co-package optics, these are still science experiments and they're very proprietary with individual vendors doing their own thing.

We embrace open CPO few years from now, but we think XPO has a 10-year run, especially at 1.60 and 3T where you need liquid cooling and you need that kind of capacity. You know, all those scale-up racks we're talking about wouldn't be possible without XPO or CPC or any one of those technologies. We see this as just as the last decade was greatly influenced by OSFP, the next decade will be greatly influenced by XPO. Remember, 99% of the optical market today that we connect to is all pluggable optics.

This is a very crucial invention and innovation, not just for Arista, but the industry at large.

I think this is a great example of how Arista enables an ecosystem, and then we profit as that ecosystem grows. What XPO unlocks is a standard interoperable multi-vendor way to get to 4x the network density and liquid cooling, which is absolutely critical for these AI use cases. Without that, you've got this huge bottleneck at the front panel, and the amount of extra rack space is required to get through OSFPs. It's. We're really enabling the future growth of our industry this way, which we benefit and others benefit as well.

Yeah. It's stunning to me. I remember when I first talked to Andy and Vijay, they said, "Oh, we think we'll get about 20 signatures," and then it was 40, and now it's north of 100. It tells me the whole consortium is coming together for things like Ethernet, IP, and standards and standardization of optics.

Our next question will come from the line of Tal Liani with Bank of America. Please go ahead.

Hello. I promised myself to be nice today, so I have a good question for you.

Deferred revenues doubled in the last year, and it went up. If I combine short-term, long-term, it went up $826 million.

It went up significantly in the last four quarters. What needs to happen? What are the conditions for to recognize deferred revenues? Meaning what needs to happen for deferred revenues to be recognized over the next few quarters? Is it about data center going live and traffic goes into data centers? Or what are the sources for the deferred revenue increase? Thanks.

Right. Right. Tal, I really do like you, so I'm gonna be nice to you not because I have to, but because I like to. I think if you remember 10 years ago, Tal, we had a similar phenomenon where in the cloud, the whole leaf-spine design was brand new. Nobody really knew how to build it or monetize it, and we were building some of the world's largest networks for Azure, etc, right? We had new products. They had new designs. They had done traditionally the access aggregation core and were now moving to the Clos fabric topology. We had some fairly lengthy qualification cycles. I would say there's a customer aspect to it and a product aspect to it.

The customer aspect to it is they need to have the space, they need to have the facilities, they need to have their, in this case, GPUs now. Back and then it used to be CPUs. They gotta have their rack and stack. Many cases, by the way, we're running into examples where it's literally they need to manually install the cables, and that takes several months, right? Thousands of people have to do that. There's certainly a customer acceptance piece of it, which it starts with being ready. There's also a new product. Many of these new products in the Arista Etherlink family, particularly for the AI, are brand new. Brand new chips, brand new software. The familiarity with it, particularly in the back end for scale-out and scale-across, is new to them.

Arista Networks (ANET) Q1 2026 Earnings Call Transcript

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