Cerebras Systems (NASDAQ:CBRS) Trading Up 15.1% – Here’s Why

Cerebras Systems Inc. (NASDAQ:CBRSGet Free Report)’s share price was up 15.1% during trading on Monday . The company traded as high as $217.88 and last traded at $231.3140. Approximately 1,034,725 shares were traded during mid-day trading, a decline of 86% from the average daily volume of 7,267,270 shares. The stock had previously closed at $201.01.

Analyst Upgrades and Downgrades

A number of equities analysts recently commented on CBRS shares. Barclays started coverage on Cerebras Systems in a report on Monday. They issued an “overweight” rating and a $280.00 target price on the stock. Morgan Stanley started coverage on Cerebras Systems in a report on Monday. They issued an “overweight” rating and a $250.00 target price on the stock. Needham & Company LLC started coverage on Cerebras Systems in a report on Monday. They issued a “buy” rating and a $300.00 target price on the stock. TD Cowen started coverage on Cerebras Systems in a report on Monday. They issued a “buy” rating and a $275.00 target price on the stock. Finally, Mizuho set a $300.00 target price on Cerebras Systems and gave the stock an “outperform” rating in a report on Monday. Nine investment analysts have rated the stock with a Buy rating, Based on data from MarketBeat.com, Cerebras Systems currently has a consensus rating of “Buy” and an average price target of $290.56.

View Our Latest Stock Report on Cerebras Systems

Cerebras Systems Stock Performance

About Cerebras Systems

(Get Free Report)

Cerebras Systems is a technology company focused on building artificial intelligence infrastructure, including hardware and software designed to accelerate deep learning and large-scale AI workloads. The company is best known for its wafer-scale processor architecture, which is intended to provide high-performance compute for training and inference applications.

In addition to its AI chips, Cerebras offers systems and related software tools that support researchers and enterprises working with machine learning models.

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