HY-World 2.0 is a multi-modal world model framework for world generation and world reconstruction. It accepts diverse input modalities — text, single-view images, multi-view images, and videos — and produces 3D world representations (meshes / Gaussian Splattings). It offers two core capabilities:
World Generation (text / single image → 3D world): syntheses high-fidelity, navigable 3D scenes through a four-stage method —— a)
Panorama Generation
with HY-Pano 2.0, b)
Trajectory Planning
with WorldNav, c)
World Expansion
with WorldStereo 2.0, and d)
World Composition
with WorldMirror 2.0 & 3DGS learning.
World Reconstruction (multi-view images / video → 3D): Powered by WorldMirror 2.0, a unified feed-forward model that simultaneously predicts depth, surface normals, camera parameters, 3D point clouds, and 3DGS attributes in a single forward pass.
HY-World 2.0 is the first open-source state-of-the-art 3D world model, delivering results comparable to closed-source methods such as Marble. We will release all model weights, code, and technical details to facilitate reproducibility and advance research in this field.
Why 3D World Models?
Existing world models, such as Genie 3, Cosmos, and HY-World 1.5 (WorldPlay+WorldCompass), generate pixel-level videos — essentially "watching a movie" that vanishes once playback ends. HY-World 2.0 takes a fundamentally different approach: it directly produces editable, persistent 3D assets (meshes / 3DGS) that can be imported into game engines like Blender/Unity/Unreal Engine/Isaac Sim — more like "building a playable game" than recording a clip. This paradigm shift natively resolves many long-standing pain points of video world models:
Video World Models
3D World Model (HY-World 2.0)
Output
Pixel videos (non-editable)
Real 3D assets — meshes / 3DGS (fully editable)
Playable Duration
Limited (typically < 1 min)
Unlimited — assets persist permanently
3D Consistency
Poor (flickering, artifacts across views)
Native — inherently consistent in 3D
Real-Time Rendering
Requires per-frame inference; high latency
Consumer GPUs can render in real time
Controllability
Weak (imprecise character control, no real physics)
Precise — zero-error control, real physics collision, accurate lighting
Inference Cost
Accumulates with every interaction
One-time generation; rendering cost ≈ 0
Engine Compatibility
✗ Video files only
✓ Directly importable into Blender / UE / Isaac Engine
$\color{IndianRed}{\textsf{Watch a video, then it's gone}}$
$\color{RoyalBlue}{\textbf{Build a world, keep it forever}}$
All above are real 3D assets (not generated videos) and entirely created by HY-World 2.0 -- captured from live real-time interaction.
✨ Highlights
Real 3D Worlds, Not Just Videos
Unlike video-only world models (e.g., Genie 3, HY World 1.5), HY-World 2.0 generates real 3D assets — 3DGS, meshes, and point clouds — that are freely explorable, editable, and directly importable into Unity / Unreal Engine / Isaac. From a single text prompt or image, create navigable 3D worlds with diverse styles: realistic, cartoon, game, and more.
Instant 3D Reconstruction from Photos & Videos
Powered by WorldMirror 2.0, a unified feed-forward model that predicts dense point clouds, depth maps, surface normals, camera parameters, and 3DGS from multi-view images or casual videos in a single forward pass. Supports flexible-resolution inference (50K–500K pixels) with SOTA accuracy. Capture a video, get a digital twin.
Interactive Character Exploration
Go beyond viewing — play inside your generated worlds. HY-World 2.0 supports first-person navigation and third-person character mode, enabling users to freely explore AI-generated streets, buildings, and landscapes with physics-based collision. Go to our product page for free try.
🧩 Architecture
Refer to our tech report for more details
A systematic pipeline of HY-World 2.0 — Panorama Generation (HY-Pano-2.0) → Trajectory Planning (WorldNav) → World Expansion (WorldStereo 2.0) → World Composition (WorldMirror 2.0 + 3DGS) — that automatically transforms text or a single image into a high-fidelity, navigable 3D world (3DGS/mesh outputs).
📝 Open-Source Plan
✅ Technical Report
✅ WorldMirror 2.0 Code & Model Checkpoints
⬜ Full Inference Code for World Generation (WorldNav + World Composition)
⬜ Panorama Generation (HY-Pano 2.0) Model & Code — HunyuanWorld 1.0 available as interim alternative
⬜ World Expansion (WorldStereo 2.0) Model & Code — WorldStereo available as interim alternative
Important: In multi-GPU mode, the number of input images must be >= the number of GPUs. For example, with --nproc_per_node=8, provide at least 8 images.
Gradio App — WorldMirror 2.0
We provide an interactive Gradio web demo for WorldMirror 2.0. Upload images or videos and visualize 3DGS, point clouds, depth maps, normal maps, and camera parameters in your browser.
Point Map Reconstruction on 7-Scenes, NRGBD, and DTU. We report the mean Accuracy and Completeness of WorldMirror under different input configurations. Bold results are best. "L / M / H" denote low / medium / high inference resolution. "+ all priors" denotes injection of camera extrinsics, camera intrinsics, and depth priors.
Method
7-Scenes (scene)
NRGBD (scene)
DTU (object)
Acc. ↓
Comp. ↓
Acc. ↓
Comp. ↓
Acc. ↓
Comp. ↓
WorldMirror 1.0
L
0.043
0.055
0.046
0.049
1.476
1.768
L + all priors
0.021
0.026
0.022
0.020
1.347
1.392
M
0.043
0.049
0.041
0.045
1.017
1.780
M + all priors
0.018
0.023
0.016
0.014
0.735
0.935
H
0.079
0.087
0.077
0.093
2.271
2.113
H + all priors
0.042
0.041
0.078
0.082
1.773
1.478
WorldMirror 2.0
L
0.041
0.052
0.047
0.058
1.352
2.009
L + all priors
0.019
0.024
0.017
0.015
1.100
1.201
M
0.033
0.046
0.039
0.047
1.005
1.892
M + all priors
0.013
0.017
0.013
0.013
0.690
0.876
H
0.037
0.040
0.046
0.053
0.845
1.904
H + all priors
0.012
0.016
0.015
0.016
0.554
0.771
WorldMirror 2.0 — Prior Comparison
Comparison with Pow3R and MapAnything under Different Prior Conditions. Results are averaged on 7-Scenes, NRGBD, and DTU datasets. Pow3R (pro) refers to the original Pow3R with Procrustes alignment.
🎬 More Examples
📖 Documentation
For detailed usage guides, parameter references, output format specifications, and prior injection instructions, see DOCUMENTATION.md.
📚 Citation
If you find HunyuanWorld 2.0 useful for your research, please cite:
bibtex
1@article{hyworld22026,
2 title={HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds},
3 author={Tencent HY-World Team},
4 journal={arXiv preprint},
5 year={2026}
6}
78@article{hunyuanworld2025tencent,
9 title={HunyuanWorld 1.0: Generating Immersive, Explorable, and Interactive 3D Worlds from Words or Pixels},
10 author={Team HunyuanWorld},
11 year={2025},
12 journal={arXiv preprint}
13}
