Stable Diffusion ยท UNet
Stable Video Diffusion XT
Stable Video Diffusion XT is a pipeline of 3 networks totalling 2.255 billion parameters, of which 1.525 billion do the actual generating. At its native 1024x576 and 25 frames the denoiser works on 230,400 latent tokens at once, and attention over that sequence is what sets the render time.
What the pipeline is made of
This is the part that separates a media model from a language model: these are separate networks, and whether they sit in memory together is your choice, not the model's.
| Component | Parameters | Published as | On disk | What it does |
|---|---|---|---|---|
| unet | 1.525B | F32 | 5.68 GB | Does the generating. Runs once per step, so it dominates both memory and time. |
| vae | 0.098B | F32 | 0.36 GB | Converts between pixels and the compressed latent space. Small, but its decode pass is a memory spike. |
| image_encoder | 0.632B | F32 | 2.35 GB | Auxiliary encoder. |
These figures were measured from the weight file headers.
Memory by precision
Everything resident, at the model's native output size, on a card large enough that precision is the only constraint.
| Precision | Peak VRAM | Quality | What it costs you |
|---|---|---|---|
| BF16 | 13.89 GB | 100% | How the weights are published. No loss, and the largest footprint. |
| FP8 | 11.88 GB | 97% | Halves the denoiser with a small, usually invisible cost. Needs Ada or newer. |
| GGUF Q8_0 | 12.01 GB | 98% | Works on any card, unlike FP8. Slightly slower than native precision. |
| GGUF Q5_K_M | 11.3 GB | 95% | A middle step when Q8 will not fit. |
| GGUF Q4_K_M | 11.08 GB | 91% | The usual way a 12B image model gets onto an 8 GB card. Detail softens. |
| NF4 | 10.98 GB | 89% | Aggressive 4-bit. Fast to load, noticeably looser on fine detail. |
Memory by arrangement
The other lever: the same weights at the same precision, moved around differently. On this model quantising is the stronger lever: the denoiser is 68% of the pipeline and stays resident whatever you rearrange.
| Arrangement | Peak VRAM | Time | How it works |
|---|---|---|---|
| Everything resident | 13.89 GB | 27 s | All components stay on the GPU. Fastest, and needs the most memory. |
| Text encoder on CPU | 13.89 GB | 28 s | The prompt is encoded once on the processor, so the encoder never touches the GPU at all. Standard practice on video models, whose encoders are often larger than their denoisers. |
| Component offload | 12.53 GB | 30 s | One component on the GPU at a time. The text encoder runs, then makes way for the denoiser. Costs a few seconds per generation. |
| Sequential offload | 10.17 GB | 2 min 36 s | Weights stream layer by layer from system RAM. Runs almost anything on almost anything, and is many times slower. |
What a bigger output costs
Both memory and time climb faster than the frame count, because attention is quadratic in the length of the latent sequence.
| Output | Latent tokens | Peak VRAM | Time |
|---|---|---|---|
| 480p, 3 seconds | 305,760 | 16.76 GB | 35 s |
| 480p, 5 seconds | 505,440 | 24.38 GB | 58 s |
| 720p, 3 seconds | 705,600 | 32.02 GB | 1 min 21 s |
| 720p, 5 seconds | 1,166,400 | 49.59 GB | 2 min 15 s |
| 720p, 10 seconds | 2,318,400 | 93.54 GB | 4 min 28 s |
Measured at BF16 with everything resident on an RTX 4090, so the columns compare with each other rather than with your machine.
Which hardware runs Stable Video Diffusion XT
98 of 118 consumer devices run it in some arrangement. Each row shows the fastest arrangement that fits on that device.
| Device | Memory | Verdict | Arrangement | Peak | Time |
|---|---|---|---|---|---|
| RTX PRO 6000 Blackwell NVIDIA | 96 GB | Comfortable | BF16 everything resident | 13.89 GB | 18 s |
| GeForce RTX 5090 NVIDIA | 32 GB | Comfortable | BF16 everything resident | 13.89 GB | 21 s |
| RTX 6000 Ada Generation NVIDIA | 48 GB | Comfortable | BF16 everything resident | 13.89 GB | 24 s |
| GeForce RTX 4090 NVIDIA | 24 GB | Comfortable | BF16 everything resident | 13.89 GB | 27 s |
| GeForce RTX 5090 Laptop NVIDIA | 24 GB | Comfortable | BF16 everything resident | 13.89 GB | 34 s |
| NVIDIA DGX Spark 128GB NVIDIA | 128 GB | Comfortable | BF16 everything resident | 13.89 GB | 35 s |
| GeForce RTX 5080 NVIDIA | 16 GB | Comfortable | BF16 everything resident | 13.89 GB | 39 s |
| GeForce RTX 4080 SUPER NVIDIA | 16 GB | Comfortable | BF16 everything resident | 13.89 GB | 42 s |
| GeForce RTX 4090 Laptop NVIDIA | 16 GB | Comfortable | BF16 everything resident | 13.89 GB | 43 s |
| GeForce RTX 4080 NVIDIA | 16 GB | Comfortable | BF16 everything resident | 13.89 GB | 45 s |
| GeForce RTX 5080 Laptop NVIDIA | 16 GB | Comfortable | BF16 everything resident | 13.89 GB | 46 s |
| GeForce RTX 5070 Ti NVIDIA | 16 GB | Comfortable | BF16 everything resident | 13.89 GB | 49 s |
| GeForce RTX 4070 Ti SUPER NVIDIA | 16 GB | Comfortable | BF16 everything resident | 13.89 GB | 49 s |
| GeForce RTX 4070 Ti NVIDIA | 12 GB | Comfortable | GGUF Q4_K_M everything resident | 11.08 GB | 54 s |
| GeForce RTX 3090 Ti NVIDIA | 24 GB | Comfortable | BF16 everything resident | 13.89 GB | 54 s |
| RTX A6000 NVIDIA | 48 GB | Comfortable | BF16 everything resident | 13.89 GB | 56 s |
| GeForce RTX 4080 Laptop NVIDIA | 12 GB | Comfortable | GGUF Q4_K_M everything resident | 11.08 GB | 58 s |
| GeForce RTX 3090 NVIDIA | 24 GB | Workable | BF16 everything resident | 13.89 GB | 1 min 1 s |
| GeForce RTX 4070 SUPER NVIDIA | 12 GB | Workable | GGUF Q4_K_M everything resident | 11.08 GB | 1 min 1 s |
| GeForce RTX 3080 Ti NVIDIA | 12 GB | Workable | GGUF Q4_K_M everything resident | 11.08 GB | 1 min 4 s |
| GeForce RTX 5070 NVIDIA | 12 GB | Workable | GGUF Q4_K_M everything resident | 11.08 GB | 1 min 10 s |
| GeForce RTX 3080 12GB NVIDIA | 12 GB | Workable | GGUF Q4_K_M everything resident | 11.08 GB | 1 min 12 s |
| GeForce RTX 4070 NVIDIA | 12 GB | Workable | GGUF Q4_K_M everything resident | 11.08 GB | 1 min 14 s |
| RTX A5000 NVIDIA | 24 GB | Workable | BF16 everything resident | 13.89 GB | 1 min 18 s |
| GeForce RTX 5060 Ti 16GB NVIDIA | 16 GB | Workable | BF16 everything resident | 13.89 GB | 1 min 30 s |
| GeForce RTX 4060 Ti 16GB NVIDIA | 16 GB | Workable | BF16 everything resident | 13.89 GB | 1 min 38 s |
| Jetson AGX Orin 32GB NVIDIA | 32 GB | Workable | BF16 everything resident | 13.89 GB | 1 min 41 s |
| Jetson AGX Orin 64GB NVIDIA | 64 GB | Workable | BF16 everything resident | 13.89 GB | 1 min 41 s |
| Radeon RX 7900 XTX AMD | 24 GB | Workable | BF16 everything resident | 13.89 GB | 1 min 42 s |
| Radeon PRO W7900 AMD | 48 GB | Workable | BF16 everything resident | 13.89 GB | 1 min 43 s |
| RTX A4000 NVIDIA | 16 GB | Workable | BF16 everything resident | 13.89 GB | 1 min 52 s |
| Radeon RX 7900 XT AMD | 20 GB | Workable | BF16 everything resident | 13.89 GB | 2 min 2 s |
| Radeon RX 9070 XT AMD | 16 GB | Workable | BF16 everything resident | 13.89 GB | 2 min 9 s |
| Radeon RX 7900 GRE AMD | 16 GB | Workable | BF16 everything resident | 13.89 GB | 2 min 16 s |
| Radeon RX 9070 AMD | 16 GB | Workable | BF16 everything resident | 13.89 GB | 2 min 40 s |
| GeForce RTX 2060 12GB NVIDIA | 12 GB | Workable | GGUF Q4_K_M everything resident | 11.08 GB | 2 min 45 s |
| Radeon RX 7800 XT AMD | 16 GB | Workable | BF16 everything resident | 13.89 GB | 2 min 47 s |
| GeForce RTX 3060 12GB NVIDIA | 12 GB | Workable | GGUF Q4_K_M everything resident | 11.08 GB | 2 min 48 s |
| Radeon RX 7700 XT AMD | 12 GB | Workable | GGUF Q4_K_M everything resident | 11.08 GB | 2 min 59 s |
| Radeon RX 6900 XT AMD | 16 GB | Workable | BF16 everything resident | 13.89 GB | 4 min 31 s |
| Radeon RX 7600 XT AMD | 16 GB | Workable | BF16 everything resident | 13.89 GB | 4 min 37 s |
| Ryzen AI Max+ 395 32GB AMD | 32 GB | Slow | BF16 everything resident | 13.89 GB | 5 min 17 s |
| Ryzen AI Max+ 395 64GB AMD | 64 GB | Slow | BF16 everything resident | 13.89 GB | 5 min 17 s |
| Ryzen AI Max+ 395 96GB AMD | 96 GB | Slow | BF16 everything resident | 13.89 GB | 5 min 17 s |
| Ryzen AI Max+ 395 128GB AMD | 128 GB | Slow | BF16 everything resident | 13.89 GB | 5 min 17 s |
Source: stabilityai/stable-video-diffusion-img2vid-xt . Downloaded 0.2 million times in the last month. See how we calculate, or browse every video model.