QumulusAI (NASDAQ:QMLS) Research Coverage Started at Compass Point

Compass Point began coverage on shares of QumulusAI (NASDAQ:QMLS) in a research report released on Friday, Marketbeat.com reports. The firm issued a buy rating and a $9.00 target price on the stock.

Several other equities research analysts have also recently weighed in on the stock. Weiss Ratings initiated coverage on shares of QumulusAI in a research report on Monday, October 12th. They issued a “sell (e-)” rating for the company. Zacks Research upgraded shares of QumulusAI to a “hold” rating in a research note on Friday, August 28th. Chardan Capital reissued a “buy” rating and set a $23.00 price objective on shares of QumulusAI in a report on Wednesday, September 30th. Finally, Wall Street Zen raised shares of QumulusAI to a “hold” rating in a research note on Saturday, July 25th. Two research analysts have rated the stock with a Buy rating, one has issued a Hold rating and one has given a Sell rating to the company’s stock. According to data from MarketBeat, the company presently has an average rating of “Hold” and a consensus target price of $16.00.

QumulusAI Stock Performance

NASDAQ:QMLS opened at $3.81 on Friday. QumulusAI has a 1-year low of $3.70 and a 1-year high of $38.00. The business has a 50-day simple moving average of $6.09. The stock has a market capitalization of $127.48 million and a price-to-earnings ratio of -1.67.

QumulusAI (NASDAQ:QMLS) last posted its earnings results on Tuesday, August 25th. The company reported ($0.72) EPS for the quarter. The business had revenue of $6.71 million for the quarter. As a group, sell-side analysts predict that QumulusAI will post -2.93 EPS for the current fiscal year.

About QumulusAI

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.