Earnings Recap — Q3 FY2026
CY Q3 2026 · Reported September 2, 2026 · Beat 6 of last 7 quarters
Hewlett Packard Enterprise Company reported Q3 FY2026 revenue of $12.20B, a beat of 1.9% against consensus, and EPS of $1.11, a beat of 19.1%.
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HPE's record orders and backlog, particularly in networking and AI systems, underscore the accelerating pace of AI infrastructure buildout, with demand outstripping supply. The expanded Oracle collaboration and hyperscaler inferencing deal signal growing investment in AI networking and inference infrastructure, which could drive further demand for networking components and servers. HPE's raised fiscal 2027 outlook suggests sustained multiyear AI infrastructure spending.
HPE delivered record Q3 FY2026 results with revenue of $12.2 billion (up 34% YoY), non-GAAP EPS of $1.11, and gross margin above 40%. Networking revenue grew 10% on a normalized basis to $2.9 billion, with orders up 36% and record Networks for AI orders of $700 million. Cloud & AI revenue grew 25% to $9 billion, with server revenue up 35% and AI systems revenue of nearly $1.6 billion. The company announced an expanded collaboration with Oracle for gigawatt-scale AI infrastructure and a post-quarter-end multibillion-dollar server deal with a hyperscaler for inferencing. Juniper integration and Catalyst transformation remain ahead of plan.
Management raised fiscal 2026 EPS guidance to $3.75-$3.85 (from prior outlook) and free cash flow to at least $3.75 billion. For fiscal 2027, they introduced a higher growth framework: consolidated revenue growth of 13%-17%, networking revenue growth of 14%-17%, Cloud & AI revenue growth of 14%-18%, operating margin of 14%-15%, EPS of $4.40-$4.60, and free cash flow of at least $5 billion. The outlook reflects record backlog, strong order momentum, and improved supply visibility from multiyear supplier agreements. Management noted supply constraints will persist but expect improved conversion in Q4 and into 2027. They also raised the fiscal 2026 Networks for AI cumulative order target to $2.5-$3 billion (from at least $2 billion).
“We booked more orders than any prior quarter in our history, resulting in a record-breaking backlog for the company.”
on Record orders and backlog
“We expect networks for AI to be a meaningful growth engine for the company. Cumulative networks for AI orders were $2.2 billion, surpassing our FY '26 target. As a result, we are increasing our year-end target to $2.5 billion to $3 billion.”
on Networks for AI order momentum
“We are not selling, Wamsi, what used to refer as a Tier 1 infrastructure. You recall that during the cloud days, we are not selling that type of infrastructure. We are selling traditional servers for AI inferencing that they will use for their own internal usage.”
on Hyperscaler deal strategy
What's giving you confidence that the current demand represents a sustained infrastructure cycle rather than customers pulling forward spend? And how much of the raised fiscal '27 outlook is related to the new hyperscaler inference and Oracle deal?
Antonio cited strong market demand, record orders, and the ramp of agentic AI and inferencing across enterprises. He noted the fiscal '27 guide does not include the AMD Helios opportunity. Marie clarified that the Oracle deal is partially included in the networking growth guide and the hyperscaler deal partially in Cloud & AI.
Networking organic growth of 10% looks light relative to orders up 36% — what's driving the gap and how should revenues catch up? Also, what is HPE providing Oracle in the expanded collaboration?
Antonio explained that supply constraints limited revenue conversion, but expects improvement in Q4 and into 2027. He detailed that Oracle will deploy HPE Juniper QFX switching (Tomahawk 6-based) and PTX routing (Express 5 silicon) at gigawatt scale, representing a multi-gigawatt, multiyear deployment.
On traditional servers, how much of the growth is ASP pass-through versus unit growth? And has the hyperscale deal changed HPE's strategy toward hyperscalers?
Antonio said units will strengthen in Q4 as supply improves, but supply will remain constrained. He clarified the hyperscaler deal is for internal AI inferencing, not traditional Tier 1 cloud infrastructure, so the strategy remains focused on profitable, enterprise-like opportunities.