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Ninja Fluid Showcases Unreal Engine 5 Real-Time Water, RTX 3050 Hits 60 FPS but Full Game Implementation Remains Limited

The Unreal Engine 5 plugin Ninja Fluid recently showcased a real-time water demonstration: water flows over sand, navigates around obstacles, and reacts to objects falling into it. The demo runs at a stable 60 FPS on an RTX 3050, but applying these effects to a full game still poses performance challenges.

Ninja Fluid展示虚幻引擎5实时水体,RTX 3050达60帧游戏实装仍受限

Over the past decade, game graphics technology has continued to advance in areas such as ray tracing, photogrammetry, and neural network super-resolution, yet water in many games is still primarily rendered using animated textures. Ninja Fluid, developed by Hungarian developer András Ketzler, focuses its demo on showcasing real-time interactions between water and scene objects.

According to developer data, running the scene on an RTX 3080 with HD settings takes approximately 0.8 milliseconds per frame for the CPU and about 2 milliseconds for the GPU, totaling less than 20% of the single-frame time budget. The demo scene also runs on a GTX 1070. These figures correspond to the demo scene and do not reflect the performance of the full game.

Currently, the full water simulation only covers an area of about 5 to 10 meters around the camera, with standard water effects used for more distant regions. Since the full game must also handle models, lighting, AI, and other elements, the cost of implementing this simulation remains high.

Ninja Fluid has been in development for several years and was used in a commercial title released in 2023. In addition to environmental water bodies, it can also be used for character ability effects. The plugin's demo version is available on itch.io and is free for indie developers to use.

Some comments recalled water effects from the Nvidia PhysX era, including those in Borderlands 2, Mafia II, and Assassin's Creed IV: Black Flag, along with the associated frame rate burden. Other developers discussed gameplay logic challenges: simulating water on the GPU and transferring data back to the CPU to calculate changes such as soil erosion or land moisture still incurs significant costs.