Home Gaming Diablo IV Patch 1.1.0c Brings Battle Pass, Stability Improvements And More

Diablo IV Patch 1.1.0c Brings Battle Pass, Stability Improvements And More

A brand-new update for Diablo IV has been released, introducing a range of fixes that enhance the gaming experience in both the Eternal realm and the Season of the Malignant.

The focus of Patch 1.1.0c is mainly on resolving bugs, addressing issues such as the unintended self-stunning caused by combining Dark Dance and Punishing Speed Malignant Powers, incorrect display of Werebear and Werewolf fur, malfunctioning controllers, and more.

In addition to bug fixes, this new Diablo IV patch also brings enhancements to the activation process for the Premium Battle Pass, as well as stability improvements. You can find the complete patch notes for Patch 1.1.0c here.

Following the release of the latest Diablo IV patch, Patch 1.1.1 is set to launch in the near future. This update will introduce various changes for the Barbarian and Sorcerer classes, additional bug fixes, and exciting new features. More details about Patch 1.1.1 will be revealed later today through a livestream hosted by the development team.

Diablo IV is now available worldwide on PC, PlayStation 5, PlayStation 4, Xbox Series X, Xbox Series S, and Xbox One. To gain deeper insight into the latest installment of this beloved series, be sure to check out Alessio’s comprehensive review.

Diablo IV marks a triumphant return for Blizzard, delivering exhilarating hack and slash action combat, a vastly improved skill system, and a captivating storyline that surpasses all previous entries. With stunning visuals, immersive audio, and smooth performance (bar occasional traversal stuttering), the game excels on many fronts. However, its adherence to traditional gameplay conventions holds it back in certain areas. The open world lacks the dynamism that some players may have expected, as events quickly become repetitive. Side content fails to offer substantial narrative depth, and the endgame replayability might suffer due to limited randomization and the absence of certain features.

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