SANA-Video - SGLang Documentation

1. Model Introduction

SANA-Video 2B 480p is a lightweight text-to-video model served through a native SGLang Diffusion pipeline. Its main advantage is deployment cost: at 2B parameters it serves 480p video from a single GPU with a plain sglang serve invocation, no parallelism flags required. The released generation profile produces 832×480 output at 81 frames and 16 FPS over 50 inference steps; a compact 17-frame, 8-step profile is covered by server CI for quick validation. Motion strength can be steered directly from the prompt with an optional motion score: N. suffix.

Model ID	Task	Default output
`Efficient-Large-Model/SANA-Video_2B_480p_diffusers`	Text to video	832x480, 81 frames at 16 FPS

2. Installation

Install SGLang with the diffusion dependencies:

Command

uv pip install "sglang[diffusion]" --prerelease=allow

See the SGLang Diffusion installation guide for platform-specific setup.

3. Serve SANA-Video

Command

sglang serve \
  --model-path Efficient-Large-Model/SANA-Video_2B_480p_diffusers \
  --port 30010

4. Generate a video

The following request uses the compact 17-frame, 8-step profile covered by server CI. Use the model defaults of 81 frames and 50 steps for the released generation profile.

Python

import time
from pathlib import Path

import requests

base_url = "http://127.0.0.1:30010"
response = requests.post(
    f"{base_url}/v1/videos",
    json={
        "model": "Efficient-Large-Model/SANA-Video_2B_480p_diffusers",
        "prompt": (
            "A red tram moves slowly through a sunlit city square while "
            "pedestrians cross behind it. motion score: 30."
        ),
        "size": "832x480",
        "num_frames": 17,
        "fps": 16,
        "num_inference_steps": 8,
        "guidance_scale": 6.0,
        "seed": 42,
    },
    timeout=60,
)
response.raise_for_status()
video_id = response.json()["id"]

while True:
    job = requests.get(f"{base_url}/v1/videos/{video_id}", timeout=30).json()
    if job["status"] == "completed":
        break
    if job["status"] == "failed":
        raise RuntimeError(job.get("error") or "Video generation failed")
    time.sleep(1)

video = requests.get(
    f"{base_url}/v1/videos/{video_id}/content",
    timeout=300,
)
video.raise_for_status()
Path("sana_video.mp4").write_bytes(video.content)

5. Request constraints

The default profile uses 832x480, 81 frames, 50 inference steps, and 16 FPS.
Frame counts are aligned to 4n+1; for example, a request for 80 frames is adjusted to 77.
Use width and height values divisible by 16.
The prompt supports an optional motion score: N. suffix to express the desired amount of motion.

​1. Model Introduction

​2. Installation

​3. Serve SANA-Video

​4. Generate a video

​5. Request constraints

1. Model Introduction

2. Installation

3. Serve SANA-Video

4. Generate a video

5. Request constraints