WorldFoundry
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3D & 4D · open generative 3D and 4D world models

Lyra

NVIDIA Spatial Intelligence Lab

WorldFoundry exposes in-tree Lyra-1 and Lyra-2 pipelines backed by vendored runtime adapters.

Runner verifiedDedicated environmentlyra

Build your run

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

worldfoundry.pipeline
Taskimage-or-video-to-world-video
Environmentlyra
DeviceCUDA 12.4
worldfoundry-eval evaluate \
  --mode model \
  --model-id lyra-1 \
  --model-runner worldfoundry:pipeline \
  --model-manifest-dir worldfoundry/data/models/catalog \
  --requests-path tmp/requests.jsonl \
  --output-dir tmp/model_eval/lyra-1 \
  --metric artifact_count \
  --json
01

Compatibility & versions

Manifest-backed recipe

Integration
integrated
Runner evidence
verified
Environment
lyra
Python
3.10
CUDA
CUDA 12.4
PyTorch
torch==2.6.0
Source revision
—
Checkpoint revision
—
Runtime profile
lyra
Pipeline binding
lyra
Runner
worldfoundry.pipeline
Pipeline target
worldfoundry.pipelines.lyra.pipeline_lyra2:LyraPipeline
Backend stage
in_tree_runtime
Runtime status
in_tree_runtime_checkpoint_and_gpu_readiness_pending
Driver status
compatible
Environment kind
Dedicated 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 lyra-1
Package constraints 37
  • attrs==25.1.0
  • better-profanity==0.7.0
  • boto3==1.35.99
  • decord==0.6.0
  • diffusers==0.32.2
  • einops==0.8.1
  • huggingface-hub==0.29.2
  • hydra-core==1.3.2
  • imageio[pyav,ffmpeg]==2.37.0
  • iopath==0.1.10
  • ipdb==0.13.13
  • loguru==0.7.2
  • mediapy==1.2.2
  • megatron-core==0.10.0
  • nltk==3.9.1
  • numpy==1.26.4
  • nvidia-ml-py==12.535.133
  • omegaconf==2.3.0
  • opencv-python==4.10.0.84
  • pandas==2.2.3
  • peft==0.14.0
  • pillow==11.1.0
  • protobuf==4.25.3
  • pynvml==12.0.0
  • pyyaml==6.0.2
  • retinaface-py==0.0.2
  • safetensors==0.5.3
  • scikit-image==0.25.2
  • sentencepiece==0.2.0
  • setuptools==76.0.0
  • termcolor==2.5.0
  • torch==2.6.0
  • torchvision==0.21.0
  • tqdm==4.66.5
  • transformers==4.49.0
  • warp-lang==1.7.2
  • openexr==3.3.5
Conda packages 12
  • python=3.10
  • pip=25.0
  • cmake
  • ninja
  • gcc=12.4.0
  • gxx=12.4.0
  • cuda=12.4
  • cuda-nvcc=12.4
  • cuda-toolkit=12.4
  • ffmpeg
  • setuptools
  • wheel
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 lyra --check-local --json
depth-anything/DA3NESTED-GIANT-LARGE-1.1
Revision
—
License
—
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 lyra-1 \
  --model-runner worldfoundry:pipeline \
  --model-manifest-dir worldfoundry/data/models/catalog \
  --requests-path tmp/requests.jsonl \
  --output-dir tmp/model_eval/lyra-1 \
  --metric artifact_count \
  --json

Input contract

FieldRecorded contract
promptRequired
imageRequired
videoRequired
actionsnavigation_actions, camera_trajectory

Artifact contract

Artifact kindFilename / path
generated_world—
generated_3d_asset—
generated_worldlyra.mp4
05

Evidence & sources

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

Integration
integrated
Runner evidence
verified
Native demo evidence
Not recorded
Validation imports
torch, torchvision, diffusers, transformers, megatron.core, transformer_engine, apex, warp
Recipe provenance
worldfoundry/data/models/catalog/three_d_four_d/lyra.yamlProjecthttps://research.nvidia.com/labs/sil/projects/lyra2/Paperhttps://openreview.net/forum?id=tIVCfVnIHoGitHubhttps://github.com/nv-tlabs/lyra