SANA-Video 2.0 · 5B · 720p · 4-Step Preview
2
21 commits
1 linked in READMEs
updated Sep 9, 2026
Project page · 4-step model · 50-step base model · Documentation · GitHub · Paper
This Space serves the independent four-step distilled
SANA-Video 2.0 5B 720p preview
checkpoint. It generates 736×1280 videos with four sampling steps, using a
five-second (81 frames at 16 FPS) or eight-second (193 frames at 24 FPS)
temporal profile. The Space uses the latest global-step-1000 tri-temporal DMD
EMA export and exposes duration, motion conditioning, and RL LoRA strength
controls. The original
50-step base model
remains available for the full T2V and TI2V pipelines and is not replaced by
this T2V-only preview.
| Setting | Value |
|---|---|
| Denoising stages | 4 |
| Resolution | 736×1280 |
| Source-tower construction size | 480 (dynamic RoPE; explicit 736×1280 bucket) |
| Duration profiles | 5 seconds: 81 frames / 16 FPS; 8 seconds: 193 frames / 24 FPS |
| CFG | 1.0 |
| Motion-score suffix | adjustable from 0 to 100; default 20 (0 disables it) |
| RL LoRA scale | adjustable from 0.3 to 1.0 in 0.1 increments; default 0.7 |
| Negative prompt | empty |
| Default demo seed | 4 |
| Generator sigma profile | sana_shift6_dpm |
| Physical sigmas | 0.9998332262, 0.9471688271, 0.8568977118, 0.6663702130 |
| Model timesteps | 999, 947, 856, 666 |
Each non-terminal stage predicts x0 and re-noises it at the next fixed sigma
with a fresh draw from the same seeded generator. flow_shift is not applied by
this sampler. Resolution, CFG, and the four-step schedule stay fixed; the UI
exposes the validated duration profiles, Motion Score, RL LoRA scale, and seed.
| Component | Source |
|---|---|
| Transformer | Efficient-Large-Model/SANA-Video_2.0_5B_720p_4step (checkpoints/SANA_Video_2.0_5B_720p_4step.pth) |
| RL scale controller | Same repository (adapters/SANA_Video_2.0_5B_720p_RL500_LoRA_rank128.pt) |
| VAE | Efficient-Large-Model/LTX-2.3-Diffusers (vae/, 128-channel latents, 8×32×32 stride) |
| Text encoder | Efficient-Large-Model/gemma-2-2b-it (decoder only, 300-token window plus CHI prompt) |
The transformer is the latest global-step-1000 full-model EMA export distilled from the ReFL step-500 initialization. It is not replaced by a LoRA and contains no optimizer, scheduler, or training-loop state. The separately published rank-128 RL LoRA is used only to adjust RL strength around that full model at runtime:
W(s) = W(scale=1) + (s - 1) × (alpha / rank) × (B_RL @ A_RL)
Scale 1.0 reproduces the uploaded full checkpoint. The default 0.7 setting is
a post-hoc adjustment around that reference, not a separately DMD-trained model.
Every scale change is reconstructed from immutable BF16 reference weights, so
repeated slider changes do not accumulate rounding error.
The diffusion/ package in this Space is
NVlabs/Sana (Apache-2.0), pruned to the modules
needed for SANA-Video 2.0 inference. FastVideoDMD4Step mirrors the stochastic
four-stage rollout used in training. Unit tests compare its timesteps, RNG
consumption, transitions, trace metadata, and BF16 behavior with a manual
reference implementation.
The tiny mmcv/ package is a compatibility stand-in that provides only the four
symbols touched by the vendored inference code (Registry, build_from_cfg,
Config/ConfigDict, and get_dist_info).
The five text-to-video examples are selected from the official
SANA-Video 2.0 project page curated set,
hosted in
Efficient-Large-Model/Sana-assets.
11 commits
10 commits
SANA-Video 2.0 · 5B · 720p · 4-Step Preview
2
21 commits
1 linked in READMEs
updated Sep 9, 2026
Project page · 4-step model · 50-step base model · Documentation · GitHub · Paper
This Space serves the independent four-step distilled
SANA-Video 2.0 5B 720p preview
checkpoint. It generates 736×1280 videos with four sampling steps, using a
five-second (81 frames at 16 FPS) or eight-second (193 frames at 24 FPS)
temporal profile. The Space uses the latest global-step-1000 tri-temporal DMD
EMA export and exposes duration, motion conditioning, and RL LoRA strength
controls. The original
50-step base model
remains available for the full T2V and TI2V pipelines and is not replaced by
this T2V-only preview.
| Setting | Value |
|---|---|
| Denoising stages | 4 |
| Resolution | 736×1280 |
| Source-tower construction size | 480 (dynamic RoPE; explicit 736×1280 bucket) |
| Duration profiles | 5 seconds: 81 frames / 16 FPS; 8 seconds: 193 frames / 24 FPS |
| CFG | 1.0 |
| Motion-score suffix | adjustable from 0 to 100; default 20 (0 disables it) |
| RL LoRA scale | adjustable from 0.3 to 1.0 in 0.1 increments; default 0.7 |
| Negative prompt | empty |
| Default demo seed | 4 |
| Generator sigma profile | sana_shift6_dpm |
| Physical sigmas | 0.9998332262, 0.9471688271, 0.8568977118, 0.6663702130 |
| Model timesteps | 999, 947, 856, 666 |
Each non-terminal stage predicts x0 and re-noises it at the next fixed sigma
with a fresh draw from the same seeded generator. flow_shift is not applied by
this sampler. Resolution, CFG, and the four-step schedule stay fixed; the UI
exposes the validated duration profiles, Motion Score, RL LoRA scale, and seed.
| Component | Source |
|---|---|
| Transformer | Efficient-Large-Model/SANA-Video_2.0_5B_720p_4step (checkpoints/SANA_Video_2.0_5B_720p_4step.pth) |
| RL scale controller | Same repository (adapters/SANA_Video_2.0_5B_720p_RL500_LoRA_rank128.pt) |
| VAE | Efficient-Large-Model/LTX-2.3-Diffusers (vae/, 128-channel latents, 8×32×32 stride) |
| Text encoder | Efficient-Large-Model/gemma-2-2b-it (decoder only, 300-token window plus CHI prompt) |
The transformer is the latest global-step-1000 full-model EMA export distilled from the ReFL step-500 initialization. It is not replaced by a LoRA and contains no optimizer, scheduler, or training-loop state. The separately published rank-128 RL LoRA is used only to adjust RL strength around that full model at runtime:
W(s) = W(scale=1) + (s - 1) × (alpha / rank) × (B_RL @ A_RL)
Scale 1.0 reproduces the uploaded full checkpoint. The default 0.7 setting is
a post-hoc adjustment around that reference, not a separately DMD-trained model.
Every scale change is reconstructed from immutable BF16 reference weights, so
repeated slider changes do not accumulate rounding error.
The diffusion/ package in this Space is
NVlabs/Sana (Apache-2.0), pruned to the modules
needed for SANA-Video 2.0 inference. FastVideoDMD4Step mirrors the stochastic
four-stage rollout used in training. Unit tests compare its timesteps, RNG
consumption, transitions, trace metadata, and BF16 behavior with a manual
reference implementation.
The tiny mmcv/ package is a compatibility stand-in that provides only the four
symbols touched by the vendored inference code (Registry, build_from_cfg,
Config/ConfigDict, and get_dist_info).
The five text-to-video examples are selected from the official
SANA-Video 2.0 project page curated set,
hosted in
Efficient-Large-Model/Sana-assets.
11 commits
10 commits