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+---
+title: Deep Learning Super Sampling (DLSS)
+authors: ["@JMS55"]
+pull_requests: [19817, 19864]
+---
+
+For users with NVIDIA RTX GPUs, Bevy now offers yet another form of anti-aliasing: DLSS.
+
+Try it out by running Bevy's anti_aliasing example: `cargo run --example anti_aliasing --features dlss --release` (after performing setup from https://github.com/JMS55/dlss_wgpu).
+
+Compared to Bevy's built-in TAA, DLSS:
+* Is much higher quality
+* Supports upscaling in addition to anti-aliasing, leading to much cheaper render times, particularly when used with GPU-heavy features like Bevy Solari
+* Requires a NVIDIA RTX GPU
+* Requires running via the Vulkan backend on Windows/Linux (no macOS, web, or mobile support)
+
+To use DLSS in your app:
+* See https://github.com/JMS55/dlss_wgpu for licensing requirements and setup instructions
+* Enable Bevy's `dlss` feature
+* Insert the `DlssProjectId` resource before `DefaultPlugins` when setting up your app
+* Add the `Dlss` component to your camera entity, optionally setting a specific `DlssPerfQualityMode` (defaults to `Auto`)
+* Optionally add sharpening via `ContrastAdaptiveSharpening`
+
+Other temporal upscalers like AMD's FidelityFX™ Super Resolution (FSR), Intel's Xe Super Sampling XeSS (XeSS), and Apple's MTLFXTemporalScaler are not integrated in this release. However they all use similiar APIs, and would not be a challenge to integrate in future releases.
+
+Support for other swapchain-related features like frame interpolation/extrapolation or latency redunction are not currently planned, but support for DLSS Ray Reconstruction for use in Bevy Solari _is_ planned for a future release.
+
+Special thanks to @cwfitzgerald for helping with the wgpu backend interop APIs.