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Video · text-to-video · video-generation

Step-Video-T2V

stepfun-ai

Runtime source is vendored in-tree; full execution remains multi-GPU/service/checkpoint gated.

PlannedUnified environmentstep-video-t2v

Build your run

Choose a recorded variant, then copy the exact setup or inspection command.

worldfoundry.pipeline
Tasktext-to-video
Environmentworldfoundry-unified-cu128
DevicePrepare Only
worldfoundry-eval evaluate \
  --mode model \
  --model-id step-video-t2v \
  --model-runner worldfoundry:pipeline \
  --model-manifest-dir worldfoundry/data/models/catalog \
  --requests-path tmp/requests.jsonl \
  --output-dir tmp/model_eval/step-video-t2v \
  --metric artifact_count \
  --json
01

Compatibility & versions

Manifest-backed recipe

Integration
planned
Runner evidence
implemented multigpu services pending
Environment
worldfoundry-unified-cu128
Python
3.10
CUDA
Prepare Only
PyTorch
—
Source revision
—
Checkpoint revision
7a2b639ca2685350e87a4df7e4026285309f7fb6
Runtime profile
step-video-t2v
Pipeline binding
step-video-t2v
Runner
worldfoundry.pipeline
Pipeline target
worldfoundry.pipelines.component_pipelines:StepVideoT2VPipeline
Backend stage
in_tree_runtime_plan
Runtime status
in_tree_step_video_runtime_ported_multigpu_services_pending
Driver status
blocked_official_requires_torch25_cuda124_or_newer_driver
Environment kind
Unified environment
02

Install environment

The environment resolver reads the recorded profile and chooses the unified or dedicated environment shown here.

bash scripts/setup/model_env_install.sh --model step-video-t2v
Package constraints 13
  • accelerate
  • transformers
  • diffusers
  • sentencepiece
  • imageio
  • numpy
  • einops
  • aiohttp
  • flask
  • flask_restful
  • ffmpeg-python
  • requests
  • xfuser
Conda packages 3
  • python
  • pip
  • ffmpeg
03

Checkpoints & assets

Run the local check before allocating compute. Gated, private, and license fields below come directly from the checkpoint manifest.

worldfoundry-eval zoo model-download --model-id step-video-t2v --check-local --json
stepfun-ai/stepvideo-t2v
Revision
7a2b639ca2685350e87a4df7e4026285309f7fb6
License
mit
Gated
—
Private
—
04

Launch & outputs

The generated command uses the shared evaluation boundary and writes durable result manifests and artifacts.

worldfoundry-eval evaluate \
  --mode model \
  --model-id step-video-t2v \
  --model-runner worldfoundry:pipeline \
  --model-manifest-dir worldfoundry/data/models/catalog \
  --requests-path tmp/requests.jsonl \
  --output-dir tmp/model_eval/step-video-t2v \
  --metric artifact_count \
  --json

Input contract

FieldRecorded contract
imageOptional
promptRequired

Artifact contract

Artifact kindFilename / path
generated_video—
generated_videostep_video_t2v.mp4
05

Evidence & sources

Catalog integration, native-demo parity, and runner parity are independent records.

Integration
planned
Runner evidence
implemented multigpu services pending
Native demo evidence
Not recorded
Validation imports
transformers, diffusers, flask
Recipe provenance
worldfoundry/data/models/catalog/video/step-video-t2v.yamlGitHubhttps://github.com/stepfun-ai/Step-Video-T2V