Earnings Recap — Q2 FY2026
CY Q3 2026 · Reported August 4, 2026 · Beat 7 of last 7 quarters
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DigitalOcean's accelerating growth and rising revenue per megawatt underscore the shift from bare-metal GPU rental to full-stack AI inference platforms. The company's ability to secure capacity ahead of demand and land large commitments signals continued strength in the AI infrastructure buildout, particularly for inference-heavy workloads. Its focus on open-weight models and software attach could pressure pure-play Neoclouds and inference providers to differentiate beyond raw capacity.
DigitalOcean delivered Q2 revenue of $281M, up 29% YoY, with record incremental ARR of $93M. AI customer ARR reached $234M, growing 212% YoY, with 85% coming from non-bare-metal services. The inference engine, launched in late April, attracted over 6,000 customers with token volume up 30x in 60 days, and open-weight models grew from ~15% to ~75% of token volume. The company also strengthened its balance sheet by retiring $472M of convertible notes and secured its first 9-figure annual revenue commitment, lifting RPO to $894M.
Management raised full-year 2026 revenue growth guidance to approximately 30% (from ~26% previously) and now expects to exit Q4 2026 at 35% or more growth. They reiterated confidence in 50%+ revenue growth for 2027, citing incremental committed capacity and strong demand. Q3 2026 revenue guidance is $304M–$307M (32%–34% YoY) with adjusted EBITDA margins of 38%–39%. They also raised adjusted free cash flow margin guidance to 11%–13% for the full year. Management emphasized disciplined capacity deployment, with 20 MW of additional capacity secured and total committed capacity now ~155 MW, and highlighted the emerging AI-native flywheel driving higher-margin, stickier services.
“We are not a GPU rental business. We are a full stack cloud platform that AI native companies depend on to build, run and scale their production AI software.”
on Differentiation from bare-metal Neoclouds
“We are not a GPU rental business. We are a full stack cloud platform that AI native companies depend on to build, run and scale their production AI software.”
on Differentiation from bare-metal Neoclouds
“We expect the incremental ARR that we get per megawatt to increase over time.”
on Revenue per megawatt trajectory
How are you meeting the demands of larger scaled customers and managing operational puts and takes to get megawatts online at the right time?
Paddy highlighted the company's track record of running a global cloud business and serving over 500,000 customers. He noted the pace of innovation (over 80 releases since April) and the addition of forward-deployed engineering to support large customers. Matt added that they work with top data center operators and leading chip manufacturers, and have managed to turn up capacity on time despite industry challenges.
What was the impact of pricing on Q2 revenue growth and the updated outlook? Also, where do you expect net leverage to be at year-end and any specific free cash flow guidance including leases?
Matt said the ~30% list price increase on GPU fleets had a modest impact on Q2 but is baked into the 2026 guide, contributing to the higher exit rate. He noted pro forma net leverage of 0.7x after the equitization, well below the 4x guideline. He confirmed the company will be free cash flow positive on any metric in 2026, with adjusted FCF margin of 11%–13%.
Can you elaborate on the 9-figure deals signed this quarter, the adoption of the 5-layer stack, and the monetization roadmap? Also, what are Kevin Van Gundy's early plans for go-to-market?
Paddy said over 70% of AI customers added this year at significant scale are already using core cloud products. He emphasized that agentic workloads require more than just GPUs or tokens, driving attach across databases, storage, and orchestration. On go-to-market, he said the focus is on landing high-quality AI-native workloads with forward-deployed engineering, not scaling sales investment yet.