---
title: "Wan2.1"
description: "Alibaba Tongyi Lab's open video family — T2V 1.3B/14B and I2V 14B at 480p/720p. The 1.3B 832×480, 81-frame route is the verified catalog backbone."
modelId: "wan2.1"
pageSource: authored
---
Wan2.1 is Alibaba Tongyi Lab's open video foundation family, and the backbone a large part of this catalog builds on — camera-control world models, action-conditioned rollouts, and later Helios-style long-video work all start from these weights. The official suite covers text-to-video at 1.3B and 14B, image-to-video 14B at 480p and 720p, plus upstream video editing and bilingual visual text (Chinese and English). This page records the four Apache-2.0 Hugging Face lines WorldFoundry actually binds: `wan2.1-t2v-1.3b`, `wan2.1-t2v-14b`, `wan2.1-i2v-14b-480p`, and `wan2.1-i2v-14b-720p`.
The technical report is [Wan: Open and Advanced Large-Scale Video Generative Models](https://arxiv.org/abs/2503.20314). Code and weights live at [Wan-Video/Wan2.1](https://github.com/Wan-Video/Wan2.1) and [Wan-AI](https://huggingface.co/Wan-AI).
## What it is for
Start on `wan2.1-t2v-1.3b`. Launch `worldfoundry-eval run wan2.1-t2v-1.3b`. Use `wan2.1-t2v-14b` or I2V 480p/720p only when you accept **Runner parity pending** on those lines.
Iterate prompts on the 1.3B line when you need a cheap, verified artifact. Wan2.1 is the default backbone when a later catalog entry (VACE, Helios, camera-control world models) says it is Wan-derived. Compare clip quality on [VBench](/docs/evaluation/benchmark-hub/vbench) and physical plausibility on [Physics-IQ](/docs/evaluation/benchmark-hub/physics-iq) — those are the suites Wan releases are commonly discussed against, not ingested WorldFoundry leaderboards.
## Runtime contract
Required `prompt`; optional `image` / `video`; `actions` is seed. Verified 1.3B T2V: **832×480, 81 frames, 50 steps, guidance 6.0, 16 fps, shift 8.0** through `Wan2p1T2VPipeline` (`wan2.1-t2v-1.3b-832x480-81f`). Artifact: `wan2.1-t2v-1.3b-832x480-81f.mp4`. 14B T2V default **1280×720**, shift **5.0**; I2V 480p **832×480 / 81 frames / 40 steps / guidance 5.0 / shift 3.0**; I2V 720p **1280×720**, shift **5.0**. Catalog tasks are `text-to-video` and `image-to-video` only.
Wan-VAE encodes **1080p of arbitrary length** so the DiT denoises in latent space. Text is UMT5. I2V needs the image-encoder checkpoint role.
## Running in WorldFoundry
Unified `worldfoundry-unified-cu128` (Python 3.11, CUDA 12.8). Stage Wan-AI checkpoints locally. License Apache-2.0. Catalog VRAM **8 GB** on the 1.3B line. Runtime integration is recorded for the family. A prior local 81-frame T2V 1.3B artifact is recorded with verified demo and runner parity; 14B T2V and both I2V lines still lack output parity. No public parity demo script is packaged, and reproducing the 1.3B artifact requires the staged checkpoint and runtime environment.
Generate the 1.3B T2V clip, then score the folder on [VBench](/docs/evaluation/benchmark-hub/vbench) `custom_input` / `aesthetic_quality` — the only VBench GPU dimension this repo verified. Read `aesthetic_quality` in `tmp/vbench/wan2.1/eval/scorecard.json`.