Date: May 5, 2026 | Source: Motley Fool (fool.com) / company press release
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Rudolph Araujo (Head of Investor Advocacy): Good afternoon, everyone, and thank you for joining us. With me on today's call are Jayshree Ullal, Arista Networks, Inc. Chairperson and Chief Executive Officer, and Chantelle Breithaupt, Arista's Chief Financial Officer. This afternoon, Arista Networks, Inc. issued a press release announcing its fiscal first quarter results for the period ending 03/31/2026. 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 and losses on strategic investments, and the income tax effect of these non-GAAP exclusions. With that, I will turn the call over to Jayshree.
Jayshree Ullal (Chairperson & CEO): Thank you, Rudy. Welcome everyone to our first quarter 2026 earnings call. Arista Networks, Inc. has experienced significant velocity in all our sectors in Q1 and we are now commanding the number one market share in high-speed switching in the greater than 10 gigabit 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. Let me 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. 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, CTC, or open co-packaged optics, CTO, as well as supporting collectives and memory acceleration.
Scale out, or horizontal scaling, involves adding more machines to a leaf-spine fabric. Arista is a shining example here with greater than 100 cumulative customers to date in 800 gigabit Ethernet deployments, and we expect the addition of 1.6 terabit 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. This demands sophisticated traffic engineering, deep routing, encryption properties, and integrated optics based on Arista EOS stack and using Arista's flagship 7800R3 or R4 series. The 7800 has established itself in this category as the premier scale-across choice.
At the recent Optical Fiber 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 terabits per pluggable module; unprecedented rack density achieving 204.8 terabits per OCP rack unit; integrated cold plate capable of cooling up to 400 watts power per module; and universality and flexibility across a range of pluggable optics, copper, as well as linear or retimed interfaces. A special kudos to Andy Bechtolsheim for driving from OSFP ten years ago to this next generation XPO.
Our enterprise business experienced strong results in Q1 2026 both in data center and campus. Our Big Switch (BNS)/Bangalore VeloCloud acquisition is also integrating well into our branch and campus strategy. 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 cost 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 multiyear purchase commitments.
We anticipate gross margin pressure due to mix and tradeoffs we are making to pay more to assure supply continuity to our customers. Nevertheless, it gives us confidence to increase our forecast 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.
Chantelle Breithaupt (CFO): Thank you, Jayshree. 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 provider 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, 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% to 63%, and down from 63.4% in the prior quarter 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. R&D spending came in strong at $271.5 million, or 10% of revenue. Our operating income for the quarter was $1.29 billion, or 47.8% of revenue. 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 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. We generated approximately $1.69 billion of cash from operations in the period, strongest in the history of Arista. DSOs came in at 64 days, down from 70 days in Q4. 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, 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. Our total deferred revenue balance was $6.2 billion, up from $5.37 billion in the prior quarter, with product deferred revenue increasing approximately $643 million versus last quarter. Accounts payable days were 54 days, down from 60 days in Q4. Capital expenditures for the quarter were $54.5 million, with approximately $40 million in CapEx related to the Santa Clara facility program, estimated to reach $180 million in 2026.
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 to $3.5 billion. For gross margin, we reiterate the range for the fiscal year of 62% to 64%, inclusive of mix and anticipated supply chain cost increases for memory and silicon. Our operating margin outlook remains at approximately 46% for the fiscal year with a tax rate expected at 21.5%.
Now, our guidance for the second quarter is as follows: revenues of approximately $2.8 billion; gross margin between 62% and 63%; operating margin between 46% and 47%; and 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%.
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Simon Leopold (Raymond James): How much revenue, if any, did scale-across contribute last year and how material is that to the $3.5 billion forecast this year?
Jayshree Ullal: Last year on scale across we were just beginning, so they were small numbers. The majority of the numbers were really scale out. That is our heritage. Scale up is virtually zero and nonexistent because it really only comes into play after the eSun spec, so consider that more a 2027–2028 number. The number will be shared between scale across and scale out, but scale across will definitely contribute at least a third of our AI number.
George Notter (Wolfe Research): Where are you in terms of scale-up rack designs with customers?
Jayshree Ullal: There is no doubt in our minds that we will have a number of racks and a number of scale-up use cases in 2027, mostly starting with 1.6T. We continue to see at least five to seven rack opportunities. There is a huge amount of liquid cooling, designs with very dense cabling options, acceleration of collectives and memory. Today scale up is mostly limited to NVLink from NVIDIA and maybe some PCI switching. The majority of the Ethernet scale up will only really happen in 2027 and 2028.
Antoine Chkaiban (New Street Research): How much does your current supply allow you to grow this year and next? Is the 28% growth guide a good reflection of how much supply you have secured?
Jayshree Ullal: The supply chain problem is not a one- or two-quarter phenomenon. We now think it is a one- or two-year phenomenon. At first, we thought it was memory. Now it is all the wafer fabrication facilities. Every chip is challenged. We started out at 20%, we were at 25%, now we are at 27.7%. Could we improve toward the tail end of the year? We will see. We think a lot of this will continue into next year and keep us constrained for the next couple of years.
Aaron Rakers (Wells Fargo): Any updated thoughts on adding one or two new 10% customers?
Jayshree Ullal: The two big ones—Microsoft and Meta—have been 10% and greater customers for over a decade, and the partnership could never be stronger. In terms of the new entrants, we still expect at least one, maybe two. They exhibit what I would call the three use cases—scale up, scale out, and scale across. The other thing we are seeing is the lack of power in sites and the demand to distribute and get a more multi-tenant scale across. So I still see one, maybe two 10% customers.
Ben Reitzes (Melius Research): What is the product-constraint drag on the $2.8B guide, and why should gross margin go back up to 63%?
Chantelle Breithaupt: The commentary about demand outstripping supply is not a Q1/Q2 issue—it is Q3, Q4, into next year. On margin, the only chance for expansion would be due to mix, which is the opportunity as we look at the second half.
Jayshree Ullal: We view this as a partnership with our customers. While we did consider and have raised prices a little bit, unlike our competitors we have not done two price increases. The price increases really come into play once our backlog starts to reduce.
Michael Ng (Goldman Sachs): Is Arista seeing networking attach opportunities for TPU or TPU-like architectures, and is Neo Cloud traction underappreciated?
Jayshree Ullal: The Neo Clouds are a very important sector because they do not always have the staff to do everything. They really lean on Arista's design expertise, EOS expertise, and a family of 22 products we have in AI. The Neo Cloud is very strong this quarter. On TPUs, in scale-across use cases we are seeing multi-tenants connecting to different AI accelerators, including GPUs. The diversity of accelerators is creating tremendous multi-accelerator opportunity.
TD Cowen (Analyst): On agentic AI—is the two-to-one front-end pressure still the correct way to think about it?
Jayshree Ullal: The largest killer application in agentic AI right now is still training; the medium is inference; and the small is enterprise. We are now seeing way more back-end activity with our large AI titans. By virtue of the back-end deployments, I do not know if we see a two-to-one to the front end anymore, but we at least see a one-to-one—wide area, CPU, and storage. Scale across in the back end has become a bigger use case than we imagined this time last year.
Tal Liani (Bank of America): Deferred revenue has doubled in the last year. What needs to happen for it to be recognized?
Jayshree Ullal: There is a customer aspect and a product aspect. The customer needs space, facilities, and GPUs, and in many cases literally need to manually install the cables, which takes several months. There is also a new product aspect—many of these new EtherLink products are brand new chips and brand new software. The qualification cycle, which used to be two to four quarters, has extended more like six to even eight quarters.
Chantelle Breithaupt: We do recognize some of it every quarter. It is not just one balance—things come in and things are recognized to the P&L.
Amit Daryanani (Evercore): As XPO ramps from OFC demos to deployments in 2027, does it change the growth profile or content per AI rack?
Jayshree Ullal: You should look at XPO as a partner to OSFP. At 400G and 800G you will be fine with OSFP. As we go to higher speeds in 2027–2028 or beyond, OSFP will run out of steam and XPO will be the new connector of choice, particularly for scale out and scale across. I do not rule out open CPO as well within a rack.
Ben Bollin (Cleveland Research): Where is enterprise in terms of consuming inference and creating agents?
Jayshree Ullal: I tend to agree with your thesis that while today we are in a training fever, a more distributed AI paradigm will emerge. We are seeing very early trials—clusters in the low thousands of GPUs, more inference-based and agentic-AI edge inference. This is the calm before the storm. As AI gets more distributed, it is going to need more high-performance compute. I think it is going to take a couple of years to fully happen.