QumulusAI (NASDAQ:QMLS) Posts Quarterly Earnings Results, Misses Expectations By $0.02 EPS

QumulusAI (NASDAQ:QMLS) issued its quarterly earnings results on Tuesday. The company reported ($0.29) earnings per share for the quarter, missing the consensus estimate of ($0.27) by ($0.02), Zacks reports. The firm had revenue of $14.76 million during the quarter, compared to the consensus estimate of $18.00 million.

Here are the key takeaways from QumulusAI’s conference call:

• Q3 revenue more than doubled sequentially to $14.8 million, up 376% year over year, as newly energized GPU capacity began billing. Adjusted EBITDA turned positive for the first time at $3.7 million.
• Q3 signings reached $352 million, lifting remaining performance obligations to $515 million; 8 MW is active and billing, with another 5.45 MW contracted. Management said demand exceeds available capacity and cited rising pricing for new-generation capacity.
• Capacity delivery remains a constraint, with some data-center timelines shifting and several newly signed or contracted blocks still awaiting service. The additional 7 MW Atlanta expansion is a right of first offer, not a committed deployment, and its timing depends on the site operator.
• The company ended the quarter with $31.1 million in cash and restricted cash against $248 million of debt and finance-lease obligations; Q3 capital expenditures were about $100 million. Management expects depreciation and interest expense to rise again in Q4 as recently deployed equipment contributes a full quarter of costs.
• QumulusAI reaffirmed its year-end targets of 18 MW of contracted capacity and $300 million of forward ARR, while reporting about $209 million of forward ARR under signed contracts. It expects $29.1 million of RPO to be recognized in Q4 and plans to revisit its forward guidance when reporting full-year results.

QumulusAI Stock Performance

QMLS stock traded down $0.26 during mid-day trading on Thursday, reaching $2.96. The company’s stock had a trading volume of 72,167 shares, compared to its average volume of 429,408. The company has a market capitalization of $99.04 million and a P/E ratio of -1.30. The business’s 50 day moving average price is $5.06. QumulusAI has a 12 month low of $2.58 and a 12 month high of $38.00.

Analysts Set New Price Targets

A number of equities analysts recently commented on QMLS shares. Chardan Capital cut their price objective on QumulusAI to $13.00 and set a “buy” rating on the stock in a research note on Wednesday. Compass Point initiated coverage on shares of QumulusAI in a report on Friday, October 16th. They set a “buy” rating and a $9.00 price target for the company. Wall Street Zen lowered shares of QumulusAI from a “hold” rating to a “sell” rating in a report on Saturday, October 17th. Weiss Ratings initiated coverage on shares of QumulusAI in a research report on Monday, October 12th. They issued a “sell (e-)” rating on the stock. Finally, B. Riley Financial dropped their price target on shares of QumulusAI from $11.00 to $9.00 and set a “buy” rating on the stock in a research report on Wednesday. Three investment analysts have rated the stock with a Buy rating, one has given a Hold rating and one has assigned a Sell rating to the stock. According to MarketBeat.com, QumulusAI currently has a consensus rating of “Hold” and an average price target of $10.33.

QumulusAI Company Profile

QumulusAI is a cloud infrastructure company specializing in rapid deployment of graphics processing unit (“GPU”)-powered solutions for artificial intelligence (“AI”) applications, serving a critical market that is often overlooked by large-scale cloud providers (“hyperscalers”), which operate massive, standardized computing infrastructures primarily serving the largest enterprises. Our platform delivers flexible, competitively priced, and customizable solutions for underserved small and mid-market customers—including machine learning teams, AI infrastructure startups, and research institutions—while also supporting the scale and complexity requirements of large enterprises, such as long-term deployments or supplemental on-demand compute capacity.