The Big Bang Theory Season 8 Cast Kaley Cuoco Shows Off Brand New Ride; Penny Honors People She Works With

Tags
Kaley Cuoco
World news
Big Bang Theory season 8

"The Big Bang Theory" season 8 cast Kaley Cuoco showed off her brand new ride after stepping out of the yoga class in Sherman Oaks, California on Wednesday.

In the series of photos from MailOnline, "The Big Bang Theory" cast Kaley Cuoco's new ride, a silver Mercedes Benz SLS AMG GT cost around a quarter of a million.

The actress was walking back to her car and dressed in printed tank top and shorts which she paired with flip-flops. She then put her belongings, along with her yoga mat, at the trunk of her vehicle.

However, the tabloid said that the price tag is just "a drop in the ocean" since the actress, who plays Penny in "The Big Bang Theory" just signed a new contract that will earn her $1 million per episode or $90 million over three years for the duration of the agreement.

Meanwhile, in a report by People magazine, "The Big Bang Theory" cast Kaley Cuoco threw a lavish party to honor her team.

The party was reserved for 20 people as event organizer Lauren Tatum called the dinner as a "a black-and-white themed party with beautiful food and music and plenty of lovely toasts."

"This was a party for people Kaley has worked with for many, many years," event designer Lauren Tatum told the magazine.

The magazine also published the menu for "The Big Bang Theory" cast Kaley Cuoco's party, which began with "brie and white chocolate puff pastry pillows." This was followed by tandoori chicken satay with garlic yogurt dipping sauce.

"For dinner, guests feasted on dishes like wine-braised short ribs, white cheddar mashed potatoes and cheese poufs with salted honey butter - all made by Meg Hall, who also handled the food for Cuoco and husband Ryan Sweeting's New Year's Eve wedding reception," the magazine added.

For dessert, the guests had "French vanilla and violet cassis macarons and salted peanut butter brownies."

Join the Discussion

Latest News

Real Time Analytics