QumulusAI (NASDAQ:QMLS) Announces Earnings Results

QumulusAI (NASDAQ:QMLS) issued its quarterly earnings results on Tuesday. The company reported ($0.29) earnings per share for the quarter, missing analysts’ consensus estimates of ($0.27) by ($0.02), Zacks reports.

QumulusAI Stock Down 1.9%

Shares of QMLS traded down $0.06 during trading hours on Tuesday, hitting $3.07. The stock had a trading volume of 312,165 shares, compared to its average volume of 434,659. QumulusAI has a 1-year low of $2.58 and a 1-year high of $38.00. The firm has a market cap of $102.72 million and a price-to-earnings ratio of -1.35. The business’s 50 day moving average is $5.16.

Analyst Upgrades and Downgrades

A number of brokerages have weighed in on QMLS. Compass Point started coverage on QumulusAI in a report on Friday, October 16th. They issued a “buy” rating and a $9.00 target price for the company. Zacks Research upgraded QumulusAI to a “hold” rating in a report on Friday, August 28th. B. Riley Financial assumed coverage on QumulusAI in a report on Wednesday, October 21st. They set a “buy” rating and a $11.00 price target on the stock. Weiss Ratings started coverage on shares of QumulusAI in a research report on Monday, October 12th. They set a “sell (e-)” rating for the company. Finally, Chardan Capital reiterated a “buy” rating and issued a $23.00 price objective on shares of QumulusAI in a research note on Wednesday, September 30th. Three research analysts have rated the stock with a Buy rating, one has given a Hold rating and one has assigned a Sell rating to the company. According to MarketBeat.com, the stock currently has an average rating of “Hold” and an average target price of $14.33.

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.