Marble ai’s performance on lower-end laptops or mobile devices depends largely on how much work is done server-side versus client-side, and how complex the rendered scenes are. Typically, the heavy lifting—turning images or videos into 3D structure—is done on the server using GPUs. The client (browser or app) is then responsible mainly for rendering the resulting 3D world and handling input. On lightweight hardware, the main bottlenecks are GPU capability, memory limits, and bandwidth for streaming scene data. If the viewer uses WebGL or WebGPU, weaker integrated GPUs may struggle with large point clouds or high-resolution textures at full quality.
To maintain good performance on these devices, developers often implement adaptive strategies: dynamic resolution scaling, level-of-detail (LOD) systems, and quality presets. For example, on a low-end laptop you might reduce point cloud density, simplify shaders, or limit the maximum frame rate to keep thermals and fan noise under control. On mobile devices, you also need to consider battery drain and thermal throttling, which can reduce performance after a few minutes of heavy 3D rendering. A common pattern is to detect device capabilities at runtime—via user-agent hints, WebGL parameter checks, or a short benchmark—and then choose an appropriate preset (for example, “low,” “medium,” “high”) for Marble ai scenes.
From a developer perspective, you should treat performance on low-end hardware as an ongoing measurement problem rather than a one-time check. Instrument your Marble ai viewer to collect metrics like frame time, dropped frames, GPU memory usage, and scene complexity. You can then group devices by performance characteristics and tweak defaults for each group. While this telemetry doesn’t strictly need a vector database, you can embed high-dimensional usage profiles (device + scene + metrics) in a system such asMilvus or Zilliz Cloud. if you want to cluster patterns at scale—for example, detecting which combinations of scene type and hardware consistently underperform and need special handling.