---
title: "Step-Video-T2V"
description: "Step-Video-T2V from StepFun: text-to-video and video-generation; Verified."
modelId: "step-video-t2v"
pageSource: generated
---
Step-Video-T2V is StepFun's large open text-to-video model (30B parameters upstream, MIT weights at stepfun-ai/stepvideo-t2v). In WorldFoundry the public pipeline is assembled from native role-based components with the shared diffusion runner — DiT, Step-LLM text encoder, CLIP, scheduler, latent initialization, and VAE decoding all execute in-process.
The recorded paper is [arXiv 2502.10248](https://arxiv.org/abs/2502.10248).
Code: [stepfun-ai/Step-Video-T2V](https://github.com/stepfun-ai/Step-Video-T2V).
## What it is for
Pick `step-video-t2v` when you want this family's text-to-video line in WorldFoundry: a prompt in, a generated clip out. Use it as the catalog T2V start rather than an editor or a world-model stepper.
Upstream: a 30B DiT with a deeply compressed Video-VAE (16x16 spatial, 8x temporal) and bilingual text encoders. This repository re-assembles the native pipeline in-process; the former xFuser and caption/VAE HTTP-service runtime is not a backend. A checkpoint-backed 204-frame GPU artifact is verified for one prompt.
Catalog tasks include text-to-video and video-generation. Catalog aliases include `step-video`, `stepvideo-t2v`, and `step_video_t2v`. Documented modalities: text in, video out.
Recorded evaluation entry points include [VBench](/docs/evaluation/benchmark-hub/vbench) (Standard open T2V quality suite).
## Runtime contract
Optional `prompt`, `negative_prompt`, `frames`, `fps`, and `height`; artifacts `generated_video` and `step_video_t2v.mp4`.
CLI task profiles: `interactive-video`. WorldFoundry binds `StepVideoT2VPipeline`.
Family status: **Verified**.
Recorded `interactive-video` defaults: frames=204, fps=25, height=544, width=992.
A checkpoint-backed 204-frame GPU artifact at 992x544 and 50 steps is verified for one prompt. Use id step-video-t2v. At 30B scale plan for serious VRAM or multi-GPU setups.
## Running in WorldFoundry
The catalog launch is `worldfoundry-eval run step-video-t2v --pipeline.task-profile interactive-video`. The command builder above switches `--pipeline.task-profile` among recorded tasks and still emits `worldfoundry-eval run`.
It runs in the unified environment `worldfoundry-unified-cu128` (Python 3.11, CUDA 12.8).
Recorded weight repositories include `stepfun-ai/stepvideo-t2v`. Prepare the environment and check local assets with `bash scripts/inference/prepare_model_infer.sh step-video-t2v`. Add `--download` to fetch missing public checkpoints.
Recorded licenses include mit; status: **Verified**.