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Recommended settings at a glance
| Use case | Resolution | Frame-rate target | Memory approach | What the evidence actually supports |
|---|---|---|---|---|
| First run focused on visual quality | 480×864 RGB, also written as 864×480 | Use the repository’s tested preset; measure rather than promise a fixed rate | Use a high-end GPU and watch peak allocation during warm-up and long sessions | The model card and repository define the output and inference paths, but do not guarantee a universal memory fit |
| Kunlun’s reference configuration | 480p output | 60 FPS headline target | An independent report attributes up to 18.5 GiB of VRAM to that setup; this is a reported peak, not a minimum specification | It is a vendor claim tied to one RTX 5090 configuration |
| RTX 5080 alternative | 864×480 | Up to 67 FPS steady state | Confirm that your scene and preset fit, then check sustained allocation | The official README says the figure excludes video I/O |
| RTX 5070 Ti alternative | 864×480 | Up to 58 FPS steady state | Leave headroom for the display and capture pipeline; verify locally | The official README says the figure excludes video I/O |
These numbers are not interchangeable benchmarks. The repository figures are steady-state measurements from the listed inference paths, while the 60-FPS figure is Kunlun Tech’s headline for a single RTX 5090 setup. A displayed game can run below either number once video capture, transfer, compositing, display synchronization, scene complexity or a different driver is included.
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What “480×864” means
The official Matrix-Game 4.0 model card defines the output as 480×864 RGB. In graphics tables and repository notes, the same dimensions are commonly written in width-by-height order as 864×480. They describe the same pixel grid, not two quality levels. Do not interpret 864×480 as an upscale mode or assume that changing the order creates a higher-resolution option.
A latent chunk produces four RGB frames after startup. That causal chunking is why a first run can show initialization behavior before its steady-state rate is reached. Measure after the model, CUDA graphs and video path have warmed up, and record startup separately if responsiveness matters.
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The model is not a conventional raster game renderer with an arbitrary resolution slider. The game engine maintains world state, physics and input; the causal video model transforms the engine’s low-poly RGB proxy, prompts and references into streaming visual chunks. The model’s resolution is therefore part of its contract. Rendering the engine proxy at a different size does not establish that the neural output is supported at that size.
Frame-rate claims: how to read them correctly
| GPU or source | Reported result | Resolution | Measurement condition | How to use it |
|---|---|---|---|---|
| RTX 5090 | 60 FPS | 480p output | Kunlun Tech headline for one configuration | Use as a reference target, not a guarantee for every scene or system |
| RTX 5080 | Up to 67 FPS | 864×480 | Official repository, steady state, video I/O excluded | A useful upper-bound reference for the repository path; your end-to-end rate can be lower |
| RTX 5070 Ti | Up to 58 FPS | 864×480 | Official repository, steady state, video I/O excluded | Expect to validate pacing and latency in your own display pipeline |
| 80 GB A100 | About 38–39 FPS | Not separately restated in the report | Independent reporting | Shows that data-center memory capacity alone does not predict consumer real-time performance |
“Up to” means the cited run reached that rate under its stated conditions; it is not a floor. The repository’s exclusion of video I/O matters because camera capture, transfers, encoding, compositing and presentation can consume both time and memory. Compare like with like: steady state against steady state, and end-to-end output against end-to-end output.
Latency is a separate metric from FPS. Independent reporting associates the RTX 5090 headline with approximately 112 ms of input-to-display latency. That figure should be treated as a report about the referenced setup, not as a model-wide promise. A stable 60-FPS counter can still feel delayed if input sampling, chunk generation or display buffering adds time.
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Quality mode
Quality mode uses the Wan VAE and two denoising steps. The extra denoising step is intended for visual quality, but it increases work per chunk. Use it when fidelity is more important than maintaining the highest interactive rate. Keep the model’s native output dimensions while comparing modes; otherwise you will not know whether a change came from the preset or from a resolution change that the model does not formally define.
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Real-time preset
The real-time preset uses TAEHV, one denoising step, an optimized single-GPU DiT path and CUDA graphs. Those choices reduce per-chunk overhead and are the appropriate starting point for interactive play. CUDA-graph capture and other initialization work can make the first measurements unrepresentative, so discard warm-up samples and report the sustained interval separately.
Choosing between them
- Start with real-time mode when input responsiveness and continuous frame delivery are the priority.
- Switch to quality mode only after confirming that its sustained frame pacing remains acceptable for your scene.
- Do not describe a quality-mode result as evidence for the real-time preset, or vice versa; they use different VAE and denoising configurations.
- Keep resolution fixed at 480×864 RGB while testing presets so that the comparison isolates the mode.
How much VRAM do you need?
There is no universal minimum published for Matrix-Game 4.0. The model card explicitly says there is no guaranteed consumer-GPU memory fit, frame rate or exact scene reconstruction. Treat any single number as a measurement from a particular scene, preset and pipeline rather than a purchase requirement.
Each scene checkpoint contains 5,001,016,512 BF16 parameters. At two bytes per BF16 parameter, the parameters alone represent roughly 10.0 billion bytes (about 9.31 GiB) before activations, temporary denoising buffers, CUDA-graph storage, the DiT runtime, video frames, engine resources and the operating system are counted. This arithmetic explains why parameter count cannot be converted into a safe card-size recommendation: runtime peaks depend on the complete execution graph.
An independent report attributes up to 18.5 GiB of VRAM to the RTX 5090 reference claim. “Up to” and the report’s setup qualification are important. It is not a guaranteed requirement for every scene, nor proof that a card with exactly that capacity will run without allocation spikes.
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Practical memory checks
- Begin with no other GPU-heavy applications running. Browsers, recording tools and overlays can consume enough memory to change whether a scene loads.
- Watch peak allocation during model load, CUDA-graph capture, the first generated chunk and a long steady-state run. The highest value is more useful than the idle value.
- Repeat the measurement in both real-time and quality modes. Their VAE and denoising paths are different.
- Reserve headroom for video input/output and presentation. Repository FPS figures exclude that work, but your system still has to perform it.
- Test the exact scene checkpoint you intend to use. A successful small scene does not establish fit for another scene.
If allocation fails, lower unrelated GPU usage first and retry the real-time preset. If it still fails, the evidence does not support assuming that a larger resolution change will solve it; the model contract remains 480×864 RGB, and a different scene or unsupported optimization may be the real cause.
GPU-by-GPU recommendations
RTX 5090: reference target, not a blanket promise
For an RTX 5090, use the native 480×864 output and begin with the real-time preset. Kunlun Tech presents 60 FPS at 480p on one RTX 5090 as its headline result. Independent reporting associates that result with up to 18.5 GiB of VRAM and approximately 112 ms input-to-display latency. Those figures describe the cited setup; they do not guarantee the same result with another scene, display path, driver, background workload or quality preset.
After warm-up, measure both generated FPS and end-to-end displayed FPS. If generated output is near the headline but displayed output is lower, investigate video I/O, synchronization and compositing before changing the model resolution.
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RTX 5080: the highest official repository figure in this comparison
The official README reports up to 67 FPS on an RTX 5080 at 864×480 in steady state, excluding video I/O. Use the repository’s single-GPU inference path, retain the native dimensions and verify sustained performance over a representative session. The number is an upper result, so a lower rate does not by itself indicate a faulty installation.
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RTX 5070 Ti: close to interactive rates in the cited path
The official README reports up to 58 FPS on an RTX 5070 Ti at 864×480 under the same steady-state, video-I/O-excluded condition. Start with real-time mode and check frame pacing rather than relying only on an average counter. A result near 58 generated FPS can still present unevenly if the display pipeline adds queues or periodic transfer stalls.
Other cards
The cited material does not establish dependable RTX 4090 or RTX 5090D benchmarks, and it does not provide a cross-scene minimum VRAM specification. Do not infer their performance from a model name, memory capacity or the A100 result. Run the exact repository path and scene on the intended hardware before treating it as a supported configuration.
A repeatable test procedure
- Fix the model contract. Set output to 480×864 RGB, recording the equivalent 864×480 notation if your benchmark table uses width-first labels.
- Choose a preset. Run the real-time preset first for interactive testing. Record whether the run uses TAEHV with one denoising step, or quality mode with Wan VAE and two steps.
- Use one GPU. Select the official single-GPU inference path for your card and close unrelated GPU workloads.
- Warm up. Allow model loading, CUDA-graph capture and initial chunk generation to finish. Keep startup time separate from steady-state measurements.
- Measure generated output. Record FPS during a stable interval and note whether the counter excludes video I/O, as the official repository measurements do.
- Measure the displayed result. Include capture, transfer, compositing and presentation to obtain an end-to-end rate. Record input-to-display latency separately if your instrumentation supports it.
- Log memory peaks. Capture allocation during load, first chunk, graph capture and a long session. Record the scene checkpoint, preset and driver with the peak.
- Stress the scene. Test rapid camera motion, occlusion, unseen geometry and a longer session. The model card warns that these conditions can cause drift or geometry errors even when the FPS counter looks healthy.
- Repeat after changes. If you change preset, scene, driver or display pipeline, repeat the warm-up and memory measurements rather than comparing partial runs.
Why ordinary game-engine settings do not transfer directly
In a conventional game, lowering internal resolution often reduces rasterization and shading work while leaving simulation rules unchanged. Matrix-Game’s architecture divides those responsibilities: the engine owns state, physics and input, while the neural model renders the visual stream from a low-poly proxy, prompts and references. The neural model therefore has a fixed native output contract and its own chunk-generation cost.
This division also explains why a high engine-side FPS counter can coexist with a lower displayed neural-video rate. The engine may update cheaply while the causal model is still generating the next four-frame chunk. Conversely, a model-rate counter that excludes video I/O can look strong while the player sees added transfer or presentation delay.
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Failure modes and fixes
The first seconds are slow
Initialization, model loading and CUDA-graph capture occur before steady state. Repeat the run after warm-up and report startup separately; do not average initialization into a claim about sustained FPS unless startup behavior is the metric you care about.
FPS is lower than the README figure
Check whether your measurement includes video I/O, whether you selected the same preset, and whether the scene is identical. The cited 5080 and 5070 Ti figures are “up to” steady-state results with video I/O excluded, so an end-to-end number below them is not unexpected.
VRAM allocation fails
Close other GPU workloads, confirm the real-time path, and inspect peak rather than idle allocation. If the same scene still fails, treat that as evidence that your card-and-scene combination is not established, because no universal fit guarantee exists.
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Check unseen geometry, rapid camera movement, occlusion and session length. The model card identifies these as conditions that can cause drift or geometry errors. A higher FPS target does not correct a scene-reconstruction failure; test a simpler or better-observed scene and document the limitation.
The displayed image feels delayed
Separate generated FPS from input-to-display latency. Inspect frame queues, transfer and presentation synchronization. The approximately 112 ms figure associated with the RTX 5090 report is setup-specific and should not be used as a universal latency expectation.
Buying and configuration decisions
| If your priority is… | Start with… | Decision rule |
|---|---|---|
| Lowest interaction delay | Real-time preset, 480×864 RGB, one high-end GPU | Accept only a configuration that sustains the required displayed rate after video I/O is included |
| Highest visual quality | Quality mode with Wan VAE and two denoising steps | Keep the native resolution and accept a lower measured rate if frame pacing remains usable |
| Predictable memory use | A tested scene and a single-GPU path | Buy only after observing peak allocation with headroom; parameter count alone is insufficient |
| Comparing GPUs | Identical scene, preset, resolution and measurement window | Separate repository-generated FPS from end-to-end displayed FPS and latency |
The safest purchase rule is empirical: test the exact scene, preset, driver and display pipeline you will use. The available evidence supports native 480×864 output and gives useful reference measurements for three GPU classes, but it does not establish a universal VRAM floor or guarantee a fixed rate across scenes.
Bottom line
Keep Matrix-Game 4.0 at 480×864 RGB, use the real-time preset for interactive play, and treat every FPS and memory number as conditional. The RTX 5090’s 60-FPS result is a vendor headline; the official repository’s 5080 and 5070 Ti figures are steady-state results that exclude video I/O. Because each scene checkpoint has about 5.001 billion BF16 parameters and the model card disclaims guaranteed consumer-GPU fit, local measurement—not a nominal VRAM number—is the only dependable final check.
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