Murea-Fast
From imagination to living worlds with agents and fast video generation.
๐ฌ Demo ยท ๐ฆ Checkpoint ยท ๐ Get started ยท ๐ ไธญๆ็ฎไป ยท โ๏ธ Contact
Murea-InWorld turns actions and imagination into audiovisual stories. Murea-Mind plans each story beat, maintains explicit world memory, and checks generated observations. Murea-Fast brings those plans to life as video with synchronized sound, conditioned on text and ordered visual references.
This repository hosts the released Murea-Fast checkpoint. The inference service, Murea-Mind application, tests, and deployment instructions are available in the code repository. Murea-Pro is evaluated in the technical report; its weights are not included in this release.
๐ฌ Demo
Watch the storytelling demo ยท Explore more worlds
โจ Highlights
- Multi-reference audiovisual generation: use ordered references for characters, objects, and locations, then describe actions and dialogue in the prompt.
- Video with synchronized sound: generate audiovisual clips with an 8-step distilled sampler.
- Continuation: extend a clip from a clean latent prefix derived from its last frames.
- Interactive worlds with Murea-Mind: turn player actions into a continuing story with persistent entities, branching histories, and shared co-op adventures.
๐ฆ Released checkpoint
| Item | Details |
|---|---|
| Model | Murea-Fast |
| File | murea-fast.safetensors |
| File size | 42,018,192,440 bytes, approximately 42.02 GB |
| Sampling | 8 steps |
| Validated output setting | 1280 ร 704 pixels, 24 fps |
| Example clip | 121 frames, approximately 5 seconds |
| Continuation | 17-frame prefix; new video frames are generated after the prefix |
| Runtime | The Murea-Fast service in the GitHub repository |
SHA-256:
1a2c0d8e23032994b52f2c67e14c930d3be8224f321c51353f0a2954ccbb9385
๐ Download and run
1. Download the weights
python -m pip install -U huggingface_hub
hf download MureaLabs/InWorld murea-fast.safetensors --local-dir ./weights
2. Get the inference code
git clone https://github.com/Murea-Labs/InWorld.git
cd InWorld/inference
Follow the deployment guide to install the GPU environment and obtain the required tokenizer, text encoder, connectors, audio/video decoders, and vocoder. The checkpoint alone is not a complete inference installation.
Set the absolute python, model_dir, checkpoint, and runtime_dir paths in configs/single-gpu.json. Set checkpoint to the downloaded murea-fast.safetensors file. Choose a configuration appropriate for the available GPUs and memory.
After completing the environment and component setup:
bash scripts/murea-fast verify /absolute/path/to/murea-fast.safetensors --sha256
bash scripts/murea-fast prepare --config configs/single-gpu.json
bash scripts/murea-fast start --config configs/single-gpu.json
curl --fail http://127.0.0.1:30260/health
For reference-conditioned generation and continuation, use the inference quick start and HTTP API reference. To play stories in the browser, follow the Murea-Mind quick start.
๐ Evaluation
The technical report reports the following results for Murea-Fast:
| Benchmark | Metric | Score |
|---|---|---|
| OpenS2V-Eval | Total | 64.98 |
| OS2V-Pro | Aggregate | 69.9 |
See the technical report and project results for the evaluation protocols and comparisons.
๐ฅ๏ธ Hardware and practical limits
The released inference service has been validated on NVIDIA H20 GPUs in one-GPU and four-GPU configurations. Runtime and memory requirements depend on reference image sizes, clip length, parallelism, and software settings. Consult the measured performance and memory results before choosing hardware.
- The published checks cover 5-second clips on one H20 and clips up to approximately 20 seconds on four 141 GB H20 GPUs. These results do not establish compatibility with smaller-memory GPUs.
- Continuation regenerates audio; continuous speech and sound across clip boundaries are not guaranteed.
- Multiple subjects can merge or lose identity, and long stories can drift. The available deployment checks do not establish quality across all prompts or worlds.
- The current service does not support frame interpolation or upscaling. Experimental acceleration settings need separate validation.
๐ ไธญๆ็ฎไป
Murea-InWorld ๅฐๆๅญ่กๅจไธๅ่ๅพๅ่ฝฌๅไธบๆ็ปญๅๅฑ็่งๅฌๆ ไบ๏ผMurea-Mind ่ด่ดฃไธ็่ฎฐๅฟใๅงๆ ่งๅไธ็ๆ็ปๆๆฃๆฅ๏ผMurea-Fast ่ด่ดฃ็ๆๅธฆๅๆญฅๅฃฐ้ณ็่ง้ขใ
ๆฌๆจกๅไปๅบๅๅธ็ๆฏ Murea-Fast ๆ้ murea-fast.safetensors๏ผMurea-Mindใๆจ็ๆๅกๅๅฎๆดไฝฟ็จๆๆกฃไฝไบ GitHub ไปฃ็ ไปๅบใ่ฎบๆไธญ่ฏๆต็ Murea-Pro ๆ้ไธๅ
ๅซๅจๆฌๆฌกๅๅธไธญใ
- ๆฏๆๆๅบๅคๅ่ๅพๆกไปถใ8 ๆญฅ่ธ้ฆ็ๆๅ่ง้ข็ปญๆฅใ
- ๅทฒ้ช่ฏ็่พๅบ่ฎพ็ฝฎไธบ 1280 ร 704ใ24 fps๏ผๆพๅญไธ่ๆถ่ฏทๅ้ ๅฎๆต่ฎฐๅฝใ
- ไธ่ฝฝๆ้ๅ๏ผ่ฟ้ๆ้จ็ฝฒๆๆกฃๅฎ่ฃ ่ฟ่ก็ฏๅขๅ้ ๅฅ็ปไปถใ
- ็ปญๆฅๆถ้ณ้ขไผ้ๆฐ็ๆ๏ผ่ทจ็ๆฎต็่ฏญ้ณๅๅฃฐ้ณ่ฟ็ปญๆงไธไฝไฟ่ฏใ
ไธญๆ้จ็ฝฒ่ฏดๆ ยท ไธญๆๆจ็ๆๅ ยท Murea-Mind ไธญๆ่ฏดๆ
๐ License
The InWorld code is released under Apache License 2.0.
The Murea-Fast weights and required base components are governed by the LTX-2.x Community License Agreement, as documented in the repository's provenance and license notice. The code license does not replace the model-weight license. See the linked agreement for its use and redistribution terms.
๐ Citation
@techreport{murealabs2026inworld,
title = {InWorld: From Imagination to Living Worlds with Agents and Fast Video Generation},
author = {{Murea Labs}},
institution = {Murea Labs},
year = {2026},
url = {https://murea.ai/page/paper/InWorld-technical-report.pdf}
}
โ๏ธ Contact
Email: [email protected]
Visit the project website or open an issue in the code repository for questions and reproducible bug reports.