In modern gaming, GPU upscaling technologies allow graphics cards to render at lower resolutions and then intelligently scale images up to higher resolutions, boosting performance without sacrificing visual quality. The main upscaling solutions are Nvidia’s DLSS, AMD’s FSR, and Intel’s XeSS, each employing unique algorithms – deep learning, spatial scaling, and AI reconstruction respectively – to deliver crisp frames. DLSS leverages dedicated Tensor Cores on GeForce RTX 20/30/40/50 series cards, FSR offers broad compatibility across AMD and competing GPUs, and XeSS works on Intel Arc GPUs, supported CPUs, and other GPUs via shader-model techniques. These upscaling technologies have revolutionized gaming by enabling smooth 4K and beyond gameplay while maintaining high frame rates, making them indispensable in modern video game development.
What Is GPU Upscaling?
GPU upscaling, also known as resolution enhancement, is the process of increasing the apparent resolution of an image or video by intelligently filling in missing pixels to match a higher display resolution. Unlike basic upscaling, which simply stretches and duplicates pixels, advanced GPU upscaling algorithms analyze image data to generate new pixel information that preserves detail and reduces artifacts. This allows games to run at lower internal render resolutions, easing the load on the GPU and resulting in higher frame rates without dramatically compromising visual fidelity.
How Does Upscaling Work in Broad Terms?
Upscaling works by taking a frame rendered at a lower resolution and using algorithms – ranging from spatial filters to machine learning models – to predict and generate data for additional pixels to create a higher resolution image. Some advanced upscalers also incorporate temporal data from previous frames, using motion vectors to align and combine pixel information over time for smoother, more consistent images. The complexity of these algorithms varies: simple spatial upscaling applies filters over neighbouring pixels, while AI-based upscalers employ neural networks trained on high-resolution images to infer missing detail and reconstruct sharper visuals.
Types of Upscaling
DLSS
Deep Learning Super Sampling (DLSS) is Nvidia’s proprietary AI-driven upscaling technology that uses dedicated Tensor Cores on RTX GPUs to upscale lower resolution frames to higher resolutions in real time. DLSS renders the game at a reduced resolution, then a trained neural network analyses spatial and temporal data – including motion vectors and information from past frames – to reconstruct a high-resolution image with enhanced detail and reduced aliasing. Since its introduction in 2018, DLSS has evolved through multiple versions – DLSS 1, DLSS 2, DLSS 3 (which added Frame Generation), and DLSS 4 (recently released with the 50 series GPU Cards) – each improving image quality, performance, and reducing artifacts. DLSS is available on all GeForce RTX 20, 30, 40, and the recently released 50 series GPUs, with Frame Generation supported on 40 series or newer, and Multi-Frame Generation exclusive to the 50 series.
DLSS Feature – Image credit: NVIDIA
FSR
FidelityFX Super Resolution (FSR) is AMD’s open-source upscaling technology that uses spatial upscaling and optional frame generation to boost performance and is available across a wide range of GPUs. FSR 1.0 performs edge reconstruction using spatial filtering, while FSR 2 and later versions leverage temporal data and advanced algorithms for higher image quality, and FSR 3 introduced Frame Generation for smoother gameplay. Because FSR does not rely on specialized AI hardware, it is compatible with AMD Radeon 5000 series and newer, Intel Arc GPUs, and Nvidia GeForce GTX and RTX GPUs – including older models that support DirectX 11, 12, or Vulkan. This broad compatibility makes FSR an attractive, free feature for gamers with various graphics cards, allowing easy implementation by developers across thousands of games.
XeSS
Xe Super Sampling (XeSS) is Intel’s AI-based upscaling solution that employs deep learning models to reconstruct high-resolution images from lower-resolution inputs in real time. XeSS analyzes neighbouring pixels and motion-compensated data to infer missing details, boosting frame rates by up to 2x while maintaining visual fidelity close to native resolution. It is fully supported on Intel Arc GPUs with XMX AI accelerators, utilizes DP4a instructions on 11th generation and newer Intel CPUs, and can also run on other GPUs through Shader Model 6.4 compatibility – extending support to a broad ecosystem of hardware. XeSS presets range from Ultra Quality to Performance mode, offering scale factors from 1.3x to 2x and render scales from 77% down to 50%, giving users flexible quality and performance trade-offs.
GPU Compatibility
DLSS is exclusive to Nvidia’s RTX lineup, requiring hardware with Tensor Cores, and only works on GeForce RTX 20 series and later GPUs – making it unavailable on older GTX cards and competing vendors’ products. FSR is vendor-agnostic, running on AMD Radeon GPUs from the RX 500 series onward, Nvidia GTX and RTX GPUs, as well as Intel Arc, due to its software-based implementation that only requires support for common graphics APIs like DirectX and Vulkan. XeSS provides best results on Intel Arc hardware but also supports non-Intel GPUs and CPUs through shader-based fallbacks, though performance may vary without dedicated AI hardware.
Impact on Gaming
Upscaling has fundamentally changed how games are developed and played, allowing developers to target higher resolutions like 4K or 8K without requiring prohibitively powerful hardware to maintain smooth frame rates. By offloading the heavy rendering workload and applying intelligent reconstruction, upscaling boosts performance, enabling richer graphics settings and smoother gameplay even on mid-range systems. This has led to more immersive gaming experiences, with features like real-time ray tracing becoming viable at higher resolutions when paired with upscaling technologies. As a result, upscaling is now a standard feature in modern game engines and GPU driver suites, and its continued evolution – such as AI-powered FSR 4 and DLSS 4 – promises further performance gains and quality improvements in future titles.
Conclusion
GPU upscaling technologies such as DLSS, FSR, and XeSS work by rendering games at lower resolutions and using sophisticated algorithms – from spatial filters to deep neural networks – to reconstruct high-resolution images with minimal performance cost. DLSS offers cutting-edge AI-driven upscaling on Nvidia’s RTX hardware, FSR provides broad compatibility and free adoption for various cards, while XeSS brings AI upscaling to Intel Arc and beyond with flexible hardware fallbacks. These upscaling solutions have transformed gaming by enabling high-fidelity visuals at accessible performance levels, paving the way for more detailed and immersive experiences on a wider range of hardware. As GPU makers continue to refine these technologies and integrate new features like multi-frame generation and AI-powered enhancements, upscaling will remain crucial for pushing the boundaries of visual quality and performance in future games.