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Use Matrix-Game 4.0 at its native 480×864 RGB output (usually written as 864×480 in benchmark tables). Treat 60 frames per second on an RTX 5090 as Kunlun Tech’s headline result, not a guaranteed baseline. The official repository reports up to 67 FPS on an RTX 5080 and up to 58 FPS on an RTX 5070 Ti in steady state at that resolution, with video input and output excluded. No published source guarantees a universal VRAM minimum; every scene checkpoint contains 5,001,016,512 BF16 parameters, and actual memory use depends on the scene, preset and runtime.
Recommended settings at a glance
There is one supported model resolution rather than a menu of conventional game resolutions. Keep the neural output at 480×864 RGB and let your display pipeline scale it if necessary. Select the quality or real-time preset according to whether visual fidelity or responsiveness matters more, then measure the exact scene on your own hardware.
| Use case | Resolution | Frame-rate expectation | Memory guidance | What the evidence means |
|---|---|---|---|---|
| Faithful first run | Native 480×864 RGB (often displayed as 864×480) | Start with the repository’s tested preset; do not promise 60 FPS | Plan around a high-end GPU and check actual fit | The model card and repository provide no universal consumer-GPU memory guarantee |
| RTX 5090 reference build | 480p-class native output | 60 FPS is Kunlun Tech’s public headline | An independent report cites peaks of up to 18.5 GiB VRAM; this is not a stated requirement | The number belongs to one reported setup and should be validated locally |
| RTX 5080 alternative | 864×480 | Up to 67 FPS steady state | Verify fit, clocks and sustained performance on the chosen scene | The official README excludes video I/O from this measurement |
| RTX 5070 Ti alternative | 864×480 | Up to 58 FPS steady state | Verify fit and sustained performance locally | The official README excludes video I/O from this measurement |
What resolution does Matrix-Game 4.0 actually produce?
The model contract is 480×864 RGB
The official model card defines the generated image as RGB with dimensions 480×864. In a height-by-width notation this is 480 pixels high and 864 pixels wide. Benchmark tables and engineering notes often write the same frame as 864×480 because they use width-by-height order. Those labels describe the same tensor; they are not two quality modes.
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One latent chunk yields four RGB frames
Matrix-Game 4.0 is causal rather than an offline video renderer. After startup, one latent chunk produces four RGB frames. The chunking scheme is why startup behavior and steady-state FPS should be reported separately: initialization, compilation and the first decoded chunk can be slower than the repeating stream.
Why ordinary game-resolution assumptions do not transfer
The engine owns state and rules
The release is engine-grounded. A game engine maintains world state, physics, input and the authoritative rules. It can draw a relatively cheap low-poly representation of that state. The causal video model then turns the low-poly RGB input, prompts and reference information into streaming visual chunks.
The neural model owns appearance
Because the neural stage is rendering the visual result, changing a conventional engine setting such as shadow quality or a swap-chain resolution is not equivalent to changing the model’s generation resolution. The engine can still affect the amount of work sent to the model, but the published model output remains 480×864 RGB. Evaluate the complete path—engine, model, decoder, display and capture—not just the engine’s internal frame counter.
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Quality mode versus real-time mode
| Mode | Decoder and denoising | Execution choices | When to use it |
|---|---|---|---|
| Quality | Wan VAE with two denoising steps | Prioritizes the quality path described by the model card | Use when visual fidelity matters more than the lowest latency |
| Real-time | TAEHV with one denoising step | Optimized single-GPU DiT execution and CUDA graphs | Use for interactive play and for the repository’s real-time throughput comparisons |
The documentation identifies these implementation differences, but it does not publish a universal VRAM saving or image-quality percentage for either mode. Do not assume that a one-step preset will fit every scene or that its FPS on one card will transfer unchanged to another. Record the selected preset whenever you record a benchmark.
How fast is it in practice?
Official repository measurements
The official repository lists single-GPU inference paths for A100, RTX 5090, RTX 5080 and RTX 5070 Ti. Its October 16 update reports up to 67 FPS on an RTX 5080 and up to 58 FPS on an RTX 5070 Ti at 864×480 in steady state. Both figures exclude video input and output. They are therefore useful for comparing the model loop, but they are not the same as end-to-end frames visible on a monitor.
Kunlun Tech’s RTX 5090 headline
Kunlun Tech publicly describes the system as 480p at 60 FPS on one RTX 5090. An independent report attributes up to 18.5 GiB of VRAM use and 112 milliseconds of input-to-display latency to that claim. Those figures describe the reported setup, not a contractual guarantee for every scene, driver, display path or session length.
Why an A100 result may look lower
Independent reporting has cited approximately 38–39 FPS on an 80 GB A100. That result should not be read as a contradiction of the newer consumer-card claims: GPU architecture, kernel optimization, CUDA-graph usage, preset, scene and I/O path all influence throughput. It does show why the GPU model and measurement method must accompany an FPS number.
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| GPU or claim | Reported rate | Measurement qualification | How to use the number |
|---|---|---|---|
| RTX 5090 | 60 FPS | Kunlun Tech headline for one setup | Reference target, not a guarantee |
| RTX 5080 | Up to 67 FPS | Official repository; steady state at 864×480, video I/O excluded | Best published repository result among the listed cards, subject to local validation |
| RTX 5070 Ti | Up to 58 FPS | Official repository; steady state at 864×480, video I/O excluded | Near-60 target in the model loop, but end-to-end output can be lower |
| 80 GB A100 | About 38–39 FPS | Independent report; conditions differ from the repository’s consumer-card measurements | Evidence that memory capacity alone does not determine speed |
How much VRAM do you need?
There is no universal minimum
The model card explicitly says there is no guaranteed consumer-GPU memory fit. It also gives no guaranteed frame rate or exact scene reconstruction. A card can have enough nominal VRAM for one checkpoint and still fail or slow down because of decoder buffers, CUDA graphs, framework allocations, the engine, display surfaces or a different scene.
What the checkpoint size tells you
Each scene checkpoint contains 5,001,016,512 BF16 parameters. At two bytes per BF16 parameter, the parameters alone represent roughly 10.0 GB (about 9.31 GiB) before runtime allocations. That arithmetic is a lower-bound estimate for parameter storage, not a recommendation for a 10 GB card. It excludes activations, attention workspaces, VAE or TAEHV buffers, CUDA-graph pools, engine resources and the operating system.
Interpreting the 18.5 GiB figure
The independently reported “up to 18.5 GiB VRAM” for the RTX 5090 setup is best treated as a measured peak for that configuration. It is not stated by the model card as a minimum, and it should not be converted into “18.5 GiB is always enough” or “18.5 GiB is required.” Leave headroom for the rest of your application and test a complete session rather than a single launch.
Memory settings that are actually defensible
- Use the native 480×864 output; there is no documented higher-resolution mode whose memory cost you can trade away.
- Choose the real-time preset when interactivity is the priority, while recognizing that its one-step TAEHV path is an execution choice, not a published memory guarantee.
- Close unrelated GPU workloads and reserve headroom for the engine, display compositor and capture tools.
- Measure peak allocation during startup and during sustained play; the first frame and a long session can have different peaks.
- Keep the exact scene checkpoint, preset, driver and runtime version with your notes so an apparent “VRAM requirement” is not generalized to another scene.
Card-by-card buying and configuration guidance
RTX 5090
Use the RTX 5090 as the reference configuration for the vendor’s 60 FPS statement. It is the only card in the published headline tied directly to 60 FPS, and the independent report adds a 112 ms input-to-display figure. Neither source promises that every scene will sustain that result. Confirm the measured end-to-end rate and VRAM peak with your own display and input path.
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RTX 5080
The repository’s “up to 67 FPS” steady-state result makes the RTX 5080 a strong alternative on paper. Because video I/O is excluded, a 67 FPS model-loop result can produce fewer displayed frames once capture, decode, composition and presentation are included. Check for sustained clocks and thermal throttling rather than relying on a short peak.
RTX 5070 Ti
The repository reports up to 58 FPS steady state at the native dimensions, also excluding video I/O. That is close to a 60 FPS target in the neural loop, but it should not be marketed as guaranteed 60 FPS on screen. Verify that your selected scene starts successfully and remains within the card’s available memory.
A100 and other cards
The official repository includes an A100 inference path, while independent reporting cites roughly 38–39 FPS on an 80 GB A100 under different conditions. The available evidence does not establish dependable results for an RTX 4090 or RTX 5090D, so those cards should be treated as unverified rather than assigned an estimated rate.
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Use the official repository’s single-GPU inference path for your card and document every variable. The following sequence keeps resolution, timing and memory claims separate.
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- Record the environment. Write down the GPU model, installed VRAM, driver, CUDA or runtime version, operating-system build, scene checkpoint and model revision.
- Set the native tensor. Configure the run for 480×864 RGB, or 864×480 when the interface labels width before height. Do not substitute a monitor resolution for the model resolution.
- Select a preset. Run the quality mode for a fidelity-oriented baseline, then the real-time mode if you need interactive latency. Note the Wan VAE/two-step or TAEHV/one-step path used.
- Warm up the pipeline. Exclude startup, compilation and first-chunk delays from a steady-state FPS average, but record startup time separately because it affects perceived responsiveness.
- Measure the model loop. Capture several steady-state intervals and report whether the counter excludes video input and output. This is the basis for comparing your result with the repository’s 67 and 58 FPS figures.
- Measure end to end. Include input capture, decoding, compositing and display presentation. If you quote latency, state whether it is input-to-display; the independently reported RTX 5090 figure is 112 ms under its stated setup.
- Watch memory over time. Log the peak during initialization, scene loading, active play and a long session. A launch that fits can still encounter drift, buffer growth or a later allocation failure.
- Repeat with the same scene. Change only one variable at a time. A different scene, camera path or prompt can alter both visual errors and resource use.
Troubleshooting by symptom
Out-of-memory error at launch
- Confirm that no other process is consuming VRAM.
- Use the official real-time path if your goal is interactive output, then retest the same scene.
- Check that you have not accidentally enabled a higher-resolution or duplicate-display path outside the documented 480×864 output.
- If the checkpoint still does not fit, the published material offers no universal workaround or minimum; record the failure rather than inferring that every scene needs the same capacity.
FPS is below the headline
- Determine whether your number includes video I/O while the repository numbers do not.
- Separate warm-up from steady state and check for thermal or power limits.
- Confirm the preset, scene checkpoint and driver match the conditions you are comparing.
- Remember that 60 FPS is a vendor claim for one RTX 5090 setup, not a promise for all cards.
Input feels delayed
Measure the complete input-to-display path rather than inferring latency from FPS. The independent RTX 5090 report cites 112 ms for its setup. Engine input handling, chunk buffering, decoding and display presentation can all contribute, so a high model-loop FPS does not automatically mean low control latency.
Geometry drifts or breaks
The model card warns that unseen geometry, rapid camera motion, occlusion and long sessions can cause drift or geometry errors. Reproduce the issue with a slower camera path and a shorter session to determine whether it is tied to motion or accumulated state, but do not treat a temporary improvement as proof that the scene is correct.
What to report when publishing your own result
A useful benchmark states all five comparison axes: output resolution, whether FPS includes video I/O, VRAM peak and available headroom, latency definition, and whether the number is a vendor claim or a reproducible repository measurement. Include the scene, preset, driver, runtime and test duration. Without those details, “60 FPS” can refer to a model-loop counter, a short peak or an end-to-end display rate, and the figures cannot be compared fairly.
Limits of the current evidence
The available documentation establishes the native output, the two presets, the listed single-GPU paths and the published measurements above. It does not establish dependable RTX 4090 or RTX 5090D benchmarks, a universal minimum VRAM requirement, or guaranteed exact reconstruction. Performance and memory can vary by scene and by the surrounding engine and display pipeline. Hardware selection should therefore be based on a local trial of the exact scene and preset rather than on a single headline number.
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