Fake frames are generated frames that modern GPUs insert between real, fully rendered frames to make gameplay look smoother and feel faster, especially in demanding games. You will usually see them offered through features like NVIDIA DLSS and AMD FSR, which use a mix of motion data, upscaling, and frame generation to boost FPS without brute-forcing every frame at full resolution. The idea sounds simple, but the results are not always the same: in some games these tools can deliver a noticeably smoother experience with minimal drawbacks, while in others they can introduce latency, shimmering, or odd artifacts that make the extra frames feel less “real.” To understand when fake frames are worth using, you first need to know what these technologies are actually doing behind the scenes.
What “fake frames” really means
The phrase “fake frames” is informal shorthand used by players to describe frame generation, the process of creating additional frames that are not fully rendered by the game engine. In technical terms, these frames are generated frames, not fake ones, but the nickname persists because they are predicted rather than traditionally rendered.
In a conventional rendering pipeline, every frame is calculated from scratch using game logic, physics, lighting, and geometry. With frame generation, the GPU renders fewer full frames and then analyzes motion data between them. Using motion vectors, depth information, and camera movement, it predicts what an intermediate frame should look like and inserts it between two real frames.
These generated frames do not make the game engine run faster, nor do they reduce CPU workload. Their purpose is purely visual: to increase the number of frames displayed on screen and make motion appear smoother. Because they are predictions, generated frames can occasionally introduce visual artifacts, such as shimmering or distortion around fast-moving objects, especially when the underlying frame rate is low or frame pacing is inconsistent.
The term “fake frames” can be misleading if taken literally. The frames are not random, and they are not fabricated without data. They are the result of informed prediction based on how the scene is already moving. When frame generation is implemented well, the difference is hard to notice outside of improved smoothness. When it is not, the generated frames can feel disconnected from player input, which is why the feature is better suited to some games than others.
How games normally render frames (the baseline)
Before frame generation makes sense, it helps to understand how games traditionally produce frames and why that approach has started to hit hard limits.
In a standard rendering pipeline, every frame is fully rendered from start to finish. There are no shortcuts. Each frame must pass through the same sequence of steps before it can be displayed on your screen.
At a high level, this is what happens for every frame:
- The CPU processes game logic, physics, AI, and player input
- The CPU sends draw calls and scene data to the GPU
- The GPU renders geometry, textures, lighting, shadows, and effects
- Post-processing is applied, and the final image is sent to the display
This entire process repeats dozens or even hundreds of times per second.
To put that in context:
- 60 FPS means the system has about 16.6 milliseconds to finish one frame
- 120 FPS cuts that time to 8.3 milliseconds
- Higher frame rates leave even less room for error
As games have evolved, the cost of rendering each frame has increased dramatically. Modern titles rely on higher resolutions, larger worlds, complex materials, advanced lighting, and ray tracing. These features do not scale efficiently.
That creates several practical limits:
- Increasing resolution sharply raises GPU workload
- Advanced lighting and ray tracing add heavy per-frame cost
- Dense scenes can overwhelm both CPU and GPU
- Performance gains slow down or stop entirely
At this point, throwing more hardware at the problem delivers diminishing returns. The GPU may not be able to render frames fast enough, or the CPU may become the bottleneck, preventing higher frame rates regardless of GPU power.
This is the environment that made upscaling and frame generation necessary. Instead of rendering every frame the hard way, modern graphics techniques aim to reduce how often full frames need to be rendered, while still maintaining smooth motion on screen.
The next step is understanding upscaling, which is the foundation that frame generation builds on.
What upscaling is and why it comes before frame generation
Once traditional rendering reaches its limits, the most straightforward way to regain performance is to render less work per frame. Upscaling is the first and most important technique used to do that.
Instead of rendering every frame at your display’s native resolution, the game renders at a lower internal resolution. That image is then reconstructed to full resolution before being displayed. Because fewer pixels are rendered in the first place, the GPU has significantly less work to do per frame.
In simple terms, upscaling works like this:
- The game renders the scene at a lower resolution
- Motion data, depth information, and previous frames are collected
- The upscaler reconstructs a higher-resolution image
- The final image is sent to the display
This approach reduces GPU workload without changing how often the game engine updates or how player input is processed. The game still runs at the same internal frame rate, but each frame is cheaper to produce.
Early upscaling techniques were simple and often resulted in blurry images. Modern upscalers are far more sophisticated. They reuse information from previous frames and analyze how objects move across the screen, allowing them to reconstruct detail that would otherwise be lost.
This is where technologies like Nvidia’s DLSS and AMD’s FSR come into play. While they differ in implementation, both aim to answer the same question: how much image quality can be preserved while rendering fewer pixels per frame? Their specific approaches and trade-offs will be covered in detail in the next section.
Upscaling is critical because frame generation builds directly on top of it. Generated frames rely on clean, stable input frames. If the upscaled image is noisy or unstable, frame generation will amplify those problems. If the upscaled image is consistent and temporally stable, generated frames blend in far more naturally.
How frame generation works (the second kind of “fake frame”)
Frame generation creates additional frames that the game engine never actually renders. Instead of drawing every frame from scratch, the GPU predicts what an in-between frame should look like and inserts it between two real, rendered frames. This increases the number of frames displayed on screen and makes motion appear smoother.
The process relies on information the game already produces. Between two rendered frames, the GPU looks at how objects moved, how the camera shifted, and how depth changed across the scene. Using this data, it estimates what the scene would look like at a point in time between those two frames and generates a new image to fill the gap.
In practical terms, frame generation works like this:
Nvidia DLSS 3 vs DLSS OFF [RTX 4090] | Direct Comparison
- The game renders two real frames
- Motion vectors and depth data describe how the scene changed
- The GPU predicts an intermediate frame
- That generated frame is inserted between the two real ones
From the display’s point of view, the frame rate increases. A game running at 60 rendered FPS can appear to run at 100 or 120 FPS once generated frames are added.
What frame generation does not do is just as important. It does not make the game engine update more often, and it does not reduce the time between player input and game logic. Input is still processed only on the real frames. Generated frames are visual estimates, not interactive moments.
This is why frame generation improves smoothness, not responsiveness. Camera motion looks fluid, animations appear cleaner, and judder is reduced, but input latency can remain the same or even increase slightly. At very low base frame rates, this trade-off becomes more noticeable, and visual artifacts become more likely.
Frame generation works best when the underlying frame rate is already stable. When there is enough real frame data to predict motion accurately, generated frames blend in naturally. When the base frame rate is low or inconsistent, prediction becomes harder, and the inserted frames can feel disconnected or unstable.
DLSS vs FSR: how NVIDIA and AMD handle upscaling and frame generation today
Both NVIDIA and AMD now use machine learning for upscaling and frame generation, and both offer these features as part of a broader performance and image-quality stack. The differences today are not about whether AI is used, but about how it is deployed across hardware generations and how consistent the results are from one system to another.
As of now, NVIDIA’s solution is DLSS 4 with the DLSS 4.5 update, while AMD’s equivalent is FSR 4 delivered through the FSR Redstone suite.
Upscaling: shared goals, different execution
Both DLSS and FSR reduce GPU workload by rendering games at a lower internal resolution and reconstructing the final image using temporal data and machine-learning models.
DLSS 4.5 introduces a second-generation Transformer-based upscaler that improves detail reconstruction, lighting accuracy, and temporal stability. Importantly, DLSS 4.5 is available on all GeForce RTX GPUs, including RTX 20, 30, 40, and 50 series cards. However, the newest DLSS models rely on FP8 precision, which is natively supported on RTX 50 series hardware and partially accelerated on RTX 40 series GPUs. Older RTX 20 and 30 series cards can still use DLSS 4.5, but with higher performance overhead, leading NVIDIA to recommend older DLSS 4 models in some cases for a better balance of performance and image quality.
FSR 4 also uses machine learning for upscaling, but only on Radeon RX 9000 GPUs built on the RDNA 4 architecture. On older Radeon hardware, FSR falls back to analytical, shader-based paths. This means FSR offers multiple quality paths depending on the GPU in use, with the AI-based path delivering noticeably better reconstruction and stability when available.
In practice:
- DLSS tends to deliver more consistent results across supported hardware, with quality scaling tied closely to GPU generation
- FSR 4 can look very competitive on RDNA 4 cards, but results vary more depending on whether the AI path is active
Frame generation: similar concepts, different scaling
Both DLSS and FSR now support frame generation, where additional frames are inserted between real, rendered frames to increase perceived smoothness.
DLSS 4.5 supports frame generation across RTX GPUs, with multi-frame generation scaling by hardware generation. RTX 50 series GPUs support advanced multi-frame generation with higher frame multipliers, while older RTX cards are limited to lower multipliers. Regardless of GPU, frame generation does not increase game logic update rates or reduce input latency. It only increases the number of frames displayed.
FSR frame generation also inserts predicted frames and now uses machine learning on RDNA 4 hardware as part of the Redstone suite. On older GPUs, it relies on non-ML paths. As with DLSS, frame generation works best when the base frame rate is already stable and sufficiently high.
Across both vendors:
- Frame generation improves visual smoothness, not responsiveness
- At low base frame rates, artifacts and latency become more noticeable
- Results vary significantly by game and engine implementation
What actually separates DLSS and FSR
The real difference today is not access versus restriction, or AI versus non-AI. It is uniformity versus flexibility.
DLSS offers a single, evolving AI pipeline that runs across all RTX GPUs, with performance and feature completeness scaling by hardware generation. FSR offers multiple execution paths, trading consistency for broader compatibility and gradual rollout of AI features on newer Radeon hardware.
DLSS remains the more mature and predictable solution overall, especially when using aggressive upscaling or frame generation. FSR has closed much of the gap and continues to improve rapidly, particularly on RDNA 4 GPUs where its AI features are fully enabled.
Are “fake frames” good or bad for video games?
“Fake frames” is a catch-all term players use to describe upscaling and frame generation together, so it makes sense to evaluate them as a single package rather than as isolated features. Whether they improve or hurt a game depends on the situation.
When used correctly, fake frames can meaningfully improve the experience. Upscaling reduces how much work the GPU must do per frame, which makes higher resolutions and advanced lighting settings practical. Frame generation then increases visual smoothness by inserting predicted frames between real ones. In games that already run at a stable base frame rate and are limited by GPU performance, this combination can deliver smoother motion with minimal downsides.
Problems appear when fake frames are used to compensate for poor underlying performance. Frame generation does not make the game engine update faster or reduce input latency. Player input is still processed only on real frames. If the base frame rate is low or unstable, generated frames increase the time between real updates, which can make controls feel sluggish. Visual artifacts such as shimmering, ghosting, or unstable edges also become more noticeable as the prediction gap widens.
This is why FPS numbers can be misleading. Upscaling increases performance by lowering rendering cost. Frame generation increases the FPS counter without increasing responsiveness. A game may report 120 FPS with frame generation enabled while still responding like a 60 FPS game. In fast-paced or competitive titles, this mismatch can feel worse than running at a lower but consistent native frame rate.
The practical takeaway is simple. Fake frames work best when they enhance an already playable experience, not when they are used to hide fundamental performance problems. Upscaling is broadly useful and often worth enabling. Frame generation is situational and should be used selectively, especially in games where responsiveness matters.
Conclusion: understanding fake frames and choosing the right hardware
“Fake frames” is an informal label for two real technologies: upscaling and frame generation. When used correctly, they allow modern games to look smoother and more detailed without requiring extreme levels of raw rendering power. When used poorly, they can inflate FPS numbers while introducing latency or visual instability. The difference comes down to understanding what each technique does, what it does not do, and when it makes sense to enable it.
Upscaling has become a core part of modern graphics pipelines and is broadly useful across most games. Frame generation is more situational. It works best when the base frame rate is already stable and the goal is smoother motion rather than faster response. Once that distinction is clear, the debate around fake frames becomes practical rather than emotional.
That same clarity applies when choosing hardware. Laptops equipped with NVIDIA GPUs give you access to the most mature DLSS implementations available today, including strong upscaling and frame generation support in modern titles. If you want a portable system that can handle demanding games and creative workloads while benefiting from AI-assisted graphics features, Acer laptops with NVIDIA GeForce GPUs are a reliable choice.
For desktop users, Acer also offers standalone graphics cards built on AMD technology. These GPUs take advantage of the latest FSR features, including AI-assisted upscaling and frame generation on supported hardware. They are a solid option for players who value broader compatibility, open standards, and strong traditional performance while still benefiting from modern reconstruction techniques powered by AMD.
Fake frames are not shortcuts or tricks. They are about making smarter trade-offs. With the right expectations and the right hardware, whether that means NVIDIA-powered Acer laptops or Acer graphics cards using AMD technology, you can make modern games look smoother, feel better, and remain playable for longer without relying on raw performance alone.
Frequently asked questions about fake frames
What are fake frames in gaming?
“Fake frames” is an informal term used to describe two technologies: upscaling and frame generation. Upscaling reconstructs each frame from a lower resolution, while frame generation inserts predicted frames between real ones. Both increase the FPS number you see, but they work in different ways.
Are fake frames the same as frame generation?
No. Frame generation is only one part of what people call fake frames. Upscaling also falls under that label because the image you see was not rendered at native resolution. Upscaling changes how frames look, while frame generation changes how many frames are displayed.
Do fake frames increase input lag?
Upscaling does not meaningfully affect input latency. Frame generation can increase latency slightly because generated frames delay the display of the most recent real frame. The effect is usually small at high base frame rates and more noticeable at low or unstable ones.
Why does FPS go up without the game feeling faster?
Frame generation increases displayed frames, not how often the game engine updates. Input and game logic still run on real frames only. This is why a game may show a high FPS number but still feel like it responds at a lower rate.
Are DLSS and FSR both using AI now?
Yes. NVIDIA DLSS has used machine learning from the start. AMD FSR now also uses machine learning with FSR 4 and the FSR Redstone suite on supported RDNA 4 hardware, while maintaining non-ML paths for older GPUs.
Is DLSS better than FSR?
DLSS is generally more consistent, especially at aggressive upscaling levels and with frame generation enabled. FSR has improved significantly and can look very close in quality modes, particularly on supported hardware. Results vary by game and settings.
Should you use fake frames in competitive games?
Usually no. Competitive and esports titles prioritize responsiveness and consistent input timing. Frame generation can make controls feel less immediate. Upscaling alone is often fine, but frame generation is best avoided in latency-sensitive games.
When do fake frames work best?
They work best when the game already runs at a stable base frame rate, is limited by GPU performance, and prioritizes visual smoothness. Single-player and cinematic games benefit the most.
Can fake frames turn an unplayable game into a playable one?
No. If the base frame rate is too low, frame generation cannot fix the underlying performance problem. In those cases, it can make the game look smoother while feeling worse to play.
Do fake frames replace the need for a powerful GPU?
No. They extend the usefulness of existing hardware and make modern visuals more practical, but they do not replace the need for sufficient base performance. Strong hardware still matters.
Recommended Products
Acer Nitro V 15 (RTX 5050)
Buy Now |
Acer Nitro V 16S AI (RTX 5060)
Buy Now |
Acer Nitro V 16 (RTX 5070)
Buy Now |
|---|
