Release RLDX-1.1 (v1.1.0)

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+rldx_overview.png filter=lfs diff=lfs merge=lfs -text

LICENSE.md

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+# RLWRLD Model License v2.0
+
+## 1. Definitions
+
+"Licensor" means RLWRLD, INC. and its affiliates.
+
+"Model" means the machine learning model, including learnt weights, parameters, configuration files, and documentation made available under this license.
+
+"Derivative Model" means all (a) modifications to the Model, (b) works based on the Model, and (c) any other derivative works of the Model, including models fine-tuned from the Model.
+
+"You" means an individual or legal entity exercising permissions granted by this license.
+
+## 2. License Grant
+
+Subject to the terms and conditions of this license, Licensor grants to You a perpetual, worldwide, non-exclusive, royalty-free license to use, reproduce, prepare derivative works of, publicly display, publicly perform, and distribute the Model and any Derivative Models.
+
+## 3. Conditions and Limitations
+
+**3.1 Use Limitations.** You may use, reproduce, or distribute the Model and any Derivative Models, or provide services for their deployment, operation, maintenance, fine-tuning, or customization, only for non-commercial purposes. "Non-commercial" means for academic research, educational, personal, or testing and evaluation purposes only, and does not include any use primarily intended for or directed toward commercial advantage or monetary compensation, or any use in the provision of commercial products or services. Notwithstanding the foregoing, You may use, reproduce or distribute the Model or any Derivative Models commercially if You obtain Licensor's prior written permission, which may be granted on separate terms determined by Licensor.
+
+For the avoidance of doubt, nothing in this license limits Licensor's own use of the Model or any Derivative Models, including for commercial purposes.
+
+**3.2 Attribution.** You must give appropriate credit to Licensor, provide a link to this license, and indicate if changes were made. You must include the following attribution notice with any distribution of the Model or Derivative Model:
+
+> "Licensed under the RLWRLD Model License v2.0"
+
+**3.3 Share-Alike.** If You distribute a Derivative Model, You must do so under this same license, or another license that includes at minimum (a) a non-commercial use limitation no less restrictive than Section 3.1, under which Licensor is the only party exempt from the limitation and the only party able to authorize commercial use, and (b) a share-alike requirement no less restrictive than this Section 3.3.
+
+**3.4 Redistribution.** You may distribute copies of the Model or Derivative Models provided that You (a) include a complete copy of this license, (b) retain all copyright, trademark, and attribution notices, and (c) comply with all conditions in this Section 3.
+
+**3.5 Use Restrictions.** You shall not use the Model or any Derivative Models for: (a) surveillance or monitoring of individuals without their consent; or (b) any use that violates applicable laws or regulations.
+
+**3.6 Trademarks.** This license does not grant any rights to use Licensor's names, logos, or trademarks, except as required for reasonable and customary use in describing the origin of the Model and reproducing the notices described in this license.
+
+**3.7 Patent Claims.** If You or Your affiliate(s) bring or threaten to bring any claim or litigation (including any claim, cross-claim, or counterclaim in a lawsuit) against any entity to enforce any patents that You allege are infringed by the Model, then any rights granted to You under this license will terminate immediately.
+
+**3.8 Termination.** If You violate any term of this license, Your rights under this license will terminate immediately.
+
+## 4. Third-Party Components
+
+The Model may include or be distributed with third-party components that are subject to separate license terms and notices. Such components are subject to their respective licenses, including any notices and disclaimers contained therein. Licensor does not grant any rights with respect to third-party components beyond those provided under the applicable third-party licenses.
+
+## 5. Disclaimer of Warranty
+
+THE MODEL IS PROVIDED "AS IS" WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WARRANTIES OF TITLE, MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, OR NONINFRINGEMENT. YOU BEAR THE RISK OF UNDERTAKING ANY ACTIVITIES UNDER THIS LICENSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OR LAWFULNESS OF USING OR REDISTRIBUTING THE MODEL, DERIVATIVE MODELS OR ANY OUTPUT OR RESULTS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE MODEL, DERIVATIVE MODELS AND ANY OUTPUT AND RESULTS.
+
+## 6. Limitation of Liability
+
+IN NO EVENT SHALL LICENSOR BE LIABLE TO YOU FOR ANY DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING OUT OF OR RELATED TO THIS LICENSE OR THE USE OR INABILITY TO USE THE MODEL, DERIVATIVE MODELS, OR ANY OUTPUTS THEREOF, EVEN IF LICENSOR HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
+
+## 7. Indemnity
+
+You shall indemnify and hold harmless Licensor from and against any claim by any third party arising out of or related to Your use or distribution of the Model, Derivative Models, or any outputs thereof.
+
+## 8. Feedback
+
+If You provide feedback, suggestions, or improvements regarding the Model, Licensor may use such feedback without restriction or compensation to You.
+
+## 9. General Provisions
+
+**9.1 Governing Law.** This license will be governed by and construed in accordance with the laws of the State of Delaware, United States, without regard to its conflict of laws rules. The UN Convention on Contracts for International Sale of Goods does not apply to this license.
+
+**9.2 License Updates.** Licensor may update this license to comply with legal and regulatory requirements at any time. You agree to either comply with any updated license or cease Your use and distribution of the Model and any Derivative Model.

NOTICE

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+RLDX-1.1 model weights
+Copyright (c) 2026 RLWRLD, INC.
+
+These weights are licensed under the RLWRLD Model License v2.0 (LICENSE.md).
+They include a component derived from the third-party model listed below,
+which remains subject to its own license.
+
+
+-------------------------------------------------------------------------------
+Qwen3-VL-8B-Instruct
+https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct
+License: Apache License, Version 2.0
+https://www.apache.org/licenses/LICENSE-2.0
+Author: Qwen Team, Alibaba Cloud
+
+The upstream repository ships no copyright line beyond its license
+designation and no NOTICE file, so there is no upstream notice content to
+reproduce under Section 4(d) of the Apache License.
+
+The vision-language backbone of these weights was initialized from
+Qwen3-VL-8B-Instruct and modified by RLWRLD through further training.

README.md

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+---
+license: other
+license_name: rlwrld-model-license-v2.0
+license_link: LICENSE.md
+library_name: transformers
+pipeline_tag: robotics
+tags:
+  - robotics
+  - vla
+  - vision-language-action
+  - manipulation
+  - flow-matching
+  - rldx
+  - video-input
+  - robocasa
+base_model: RLWRLD/RLDX-1.1-PT
+---
+
+# RLDX-1.1-FT-ROBOCASA
+
+[Paper](https://arxiv.org/abs/2605.03269)  ·  [Project page](https://rlwrld.ai/rldx-1)  ·  [Code](https://github.com/RLWRLD/RLDX-1/tree/v1.1.0)  ·  [Models](https://huggingface.co/collections/RLWRLD/rldx-11)
+
+<p align="center">
+<img src="rldx_overview.png" width="100%" alt="RLDX-1.1 overview">
+</p>
+
+**RLDX-1.1** is a Vision-Language-Action model (VLA) for human-like dexterous manipulation. Beyond the *versatile intelligence* inherited from pre-trained VLM backbones, RLDX-1.1 adds three **functional capabilities** — motion awareness, long-term memory, and physical sensing — through a unified **Multi-Stream Action Transformer (MSAT)** architecture, a synthetic-augmented training pipeline, and a real-time inference stack.
+
+This repository hosts **`RLDX-1.1-FT-ROBOCASA`**, [`RLWRLD/RLDX-1.1-PT`](https://huggingface.co/RLWRLD/RLDX-1.1-PT) fine-tuned on **RoboCasa Kitchen (24 tasks)** with 4-frame video input.
+
+## What's New in RLDX-1.1
+
+- **Better performance.** A refined RLDX-1 corpus plus a broad collection of open-source robot datasets gives a stronger pre-training foundation. Video-input fine-tunes enable the motion module, which RLDX-1 video checkpoints did not use.
+- **Smoother actions in low DoF.** Padded action dimensions are masked from pre-training on, so flow-matching noise no longer reaches unused joints. Keep `mask_padded_action_dims=True` when fine-tuning from this checkpoint.
+- **Faster training and inference.** Training is 2.27× faster than RLDX-1. Inference is up to 9.4× faster on H100 and 3.7× on RTX 5090, with fp8 on every supported GPU and nvfp4 on Jetson Thor, GB10 and RTX 5090. See [Optimization](https://github.com/RLWRLD/RLDX-1/blob/v1.1.0/docs/optimization.md).
+
+Details are in the [README](https://github.com/RLWRLD/RLDX-1/tree/v1.1.0#whats-new-in-rldx-11).
+
+<p align="center">
+<img src="overview_architecture.png" width="90%" alt="RLDX-1.1 architecture">
+</p>
+
+## Model Family
+
+**Video input**
+
+| Checkpoint | Type | Description |
+|---|---|---|
+| [`RLDX-1.1-PT`](https://huggingface.co/RLWRLD/RLDX-1.1-PT) | Base | Pre-trained |
+| **`RLDX-1.1-FT-ROBOCASA`** (this repo) | Fine-tuned | RoboCasa Kitchen |
+| [`RLDX-1.1-FT-GR1`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-GR1) | Fine-tuned | GR-1 Tabletop |
+| [`RLDX-1.1-FT-LIBERO`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-LIBERO) | Fine-tuned | LIBERO |
+| [`RLDX-1.1-FT-RC365`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-RC365) | Fine-tuned | RoboCasa365 |
+
+**Image input**
+
+| Checkpoint | Type | Description |
+|---|---|---|
+| [`RLDX-1.1-PT-IMG`](https://huggingface.co/RLWRLD/RLDX-1.1-PT-IMG) | Base | Pre-trained |
+| [`RLDX-1.1-FT-ROBOCASA-IMG`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-ROBOCASA-IMG) | Fine-tuned | RoboCasa Kitchen |
+| [`RLDX-1.1-FT-GR1-IMG`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-GR1-IMG) | Fine-tuned | GR-1 Tabletop |
+| [`RLDX-1.1-FT-LIBERO-IMG`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-LIBERO-IMG) | Fine-tuned | LIBERO |
+| [`RLDX-1.1-FT-RC365-IMG`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-RC365-IMG) | Fine-tuned | RoboCasa365 |
+
+RLDX-1 checkpoints also load with this codebase; see [Model Checkpoints](https://github.com/RLWRLD/RLDX-1/tree/v1.1.0#model-checkpoints).
+
+## Performance
+
+| Benchmark | Success Rate (%) |
+|---|---|
+| RoboCasa Kitchen | **72.3** |
+
+Evaluation guide: [RoboCasa Kitchen](https://github.com/RLWRLD/RLDX-1/blob/v1.1.0/run_scripts/eval/robocasa_kitchen/README.md). Training recipe: [`finetune_robocasa.sh`](https://github.com/RLWRLD/RLDX-1/blob/v1.1.0/run_scripts/train/benchmarks/finetune_robocasa.sh) with `VARIANT=video`.
+
+The comparison with other VLAs is in the [README](https://github.com/RLWRLD/RLDX-1/tree/v1.1.0#comparison-with-other-vlas).
+
+## Quick Start
+
+```bash
+git clone --branch v1.1.0 https://github.com/RLWRLD/RLDX-1.git
+cd RLDX-1
+uv sync --python 3.10
+```
+
+Load a checkpoint and predict an action chunk in-process:
+
+```python
+from rldx.serving.policy import load_policy
+from rldx.data.embodiment_tags import EmbodimentTag
+
+policy = load_policy(
+    model_path="RLWRLD/RLDX-1.1-FT-ROBOCASA",
+    embodiment_tag=EmbodimentTag.GENERAL_EMBODIMENT,
+    device="cuda:0",
+)
+
+# observation: {"video": {...}, "state": {...}, "language": {...}}
+actions, info = policy.get_action(observation)
+```
+
+Serve the same policy over ZeroMQ for simulator rollouts or a real robot:
+
+```bash
+uv run python rldx/eval/run_rldx_server.py \
+    --model-path RLWRLD/RLDX-1.1-FT-ROBOCASA \
+    --embodiment-tag GENERAL_EMBODIMENT \
+    --host 0.0.0.0 --port 20000
+```
+
+Runtime profiles (fp8 / nvfp4, CUDA graphs) and Real-Time Chunking are described in [`docs/inference_server.md`](https://github.com/RLWRLD/RLDX-1/blob/v1.1.0/docs/inference_server.md).
+
+## Model Details
+
+- **Architecture:** Multi-Stream Action Transformer (MSAT) with a Qwen3-VL vision-language backbone and cognition tokens, trained with flow matching.
+- **Inputs:** RGB video, 4 frames per camera (stride 2), proprioceptive state, and a language instruction.
+- **Outputs:** action chunks of 16 steps.
+- **Modules:** motion module on (inserted at VLM layer 9); memory and physics off. Padded action dimensions are masked (`mask_padded_action_dims=True`).
+- **Embodiment tag:** `GENERAL_EMBODIMENT`.
+- **Base model:** [`RLWRLD/RLDX-1.1-PT`](https://huggingface.co/RLWRLD/RLDX-1.1-PT).
+- **Backbone:** initialized from [`Qwen/Qwen3-VL-8B-Instruct`](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) and modified through further training (see [Third-Party Notice](#third-party-notice)).
+- **Parameters:** 6.6B.
+
+A walkthrough of the architecture is in [`docs/architecture.md`](https://github.com/RLWRLD/RLDX-1/blob/v1.1.0/docs/architecture.md).
+
+## Intended Use and Limitations
+
+**Intended use.** Research on robotic manipulation, fine-tuning on custom embodiments, simulation benchmarking, and non-commercial real-robot deployment under the RLWRLD Model License v2.0. Commercial use requires prior written permission from RLWRLD (§3.1).
+
+**Out of scope.** Surveillance or monitoring of individuals without their consent, and any use that violates applicable laws or regulations (§3.5 of [`LICENSE.md`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-ROBOCASA/blob/main/LICENSE.md)).
+
+**Limitations.** Results are reported on the RoboCasa Kitchen benchmark. Other scenes, objects, or embodiments are not guaranteed; for a different robot or dataset, fine-tune from [`RLWRLD/RLDX-1.1-PT`](https://huggingface.co/RLWRLD/RLDX-1.1-PT) instead.
+
+## Third-Party Notice
+
+The vision-language backbone of this checkpoint was initialized from [Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) by the Qwen Team, Alibaba Cloud, licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0), and was modified by RLWRLD through further training. See [`NOTICE`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-ROBOCASA/blob/main/NOTICE).
+
+## Citation
+
+```bibtex
+@article{rldx2026,
+  title={RLDX-1 Technical Report},
+  author={Dongyoung Kim and Huiwon Jang and Myungkyu Koo and Suhyeok Jang and Taeyoung Kim and others},
+  year={2026},
+  journal={arXiv preprint arXiv:2605.03269},
+  eprint={2605.03269},
+  archivePrefix={arXiv}
+}
+```
+
+Please also cite the Qwen3-VL backbone and RoboCOIN, whose data was used in pre-training.
+
+```bibtex
+@misc{qwen3technicalreport,
+      title={Qwen3 Technical Report},
+      author={Qwen Team},
+      year={2025},
+      eprint={2505.09388},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2505.09388},
+}
+
+@article{robocoin,
+    title={RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation},
+    author={Shihan Wu, Xuecheng Liu, Shaoxuan Xie, Pengwei Wang, Xinghang Li, Bowen Yang, Zhe Li, Kai Zhu, Hongyu Wu, Yiheng Liu, Zhaoye Long, Yue Wang, Chong Liu, Dihan Wang, Ziqiang Ni, Xiang Yang, You Liu, Ruoxuan Feng, Runtian Xu, Lei Zhang, Denghang Huang, Chenghao Jin, Anlan Yin, Xinlong Wang, Zhenguo Sun, Junkai Zhao, Mengfei Du, Mingyu Cao, Xiansheng Chen, Hongyang Cheng, Xiaojie Zhang, Yankai Fu, Ning Chen, Cheng Chi, Sixiang Chen, Huaihai Lyu, Xiaoshuai Hao, Yequan Wang, Bo Lei, Dong Liu, Xi Yang, Yance Jiao, Tengfei Pan, Yunyan Zhang, Songjing Wang, Ziqian Zhang, Xu Liu, Ji Zhang, Caowei Meng, Zhizheng Zhang, Jiyang Gao, Song Wang, Xiaokun Leng, Zhiqiang Xie, Zhenzhen Zhou, Peng Huang, Wu Yang, Yandong Guo, Yichao Zhu, Suibing Zheng, Hao Cheng, Xinmin Ding, Yang Yue, Huanqian Wang, Chi Chen, Jingrui Pang, YuXi Qian, Haoran Geng, Lianli Gao, Haiyuan Li, Bin Fang, Gao Huang, Yaodong Yang, Hao Dong, He Wang, Hang Zhao, Yadong Mu, Di Hu, Hao Zhao, Tiejun Huang, Shanghang Zhang, Yonghua Lin, Zhongyuan Wang and Guocai Yao},
+    journal={arXiv preprint arXiv:2511.17441},
+    url = {https://arxiv.org/abs/2511.17441},
+    year={2025}
+}
+```
+
+## License
+
+Released under the **RLWRLD Model License v2.0**, a non-commercial license with attribution and share-alike terms. See [`LICENSE.md`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-ROBOCASA/blob/main/LICENSE.md) for the full text. By using this model you agree to those terms, including the use restrictions in §3.5. The Qwen3-VL component remains subject to the Apache License 2.0 as described in [`NOTICE`](https://huggingface.co/RLWRLD/RLDX-1.1-FT-ROBOCASA/blob/main/NOTICE).

config.json

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+{
+  "dtype": "bfloat16",
+  "architectures": [
+    "RLDX"
+  ],
+  "transformers_version": "4.57.0",
+  "attn_implementation": null,
+  "model_type": "RLDX-1",
+  "model_dtype": "bfloat16",
+  "model_name": "RLWRLD/RLDX-1-VLM",
+  "backbone_model_type": "vtc_qwen3_vl",
+  "model_revision": null,
+  "tune_top_llm_layers": 4,
+  "backbone_embedding_dim": 4096,
+  "tune_llm": false,
+  "tune_visual": false,
+  "select_layer": 18,
+  "reproject_vision": false,
+  "use_flash_attention": true,
+  "load_bf16": true,
+  "freeze_cog_tokens": false,
+  "image": {
+    "max_area": 65536,
+    "resize_m": 32,
+    "crop_fraction": null
+  },
+  "augmentation": {
+    "rotation_angle": null,
+    "color_jitter": {
+      "brightness": 0.3,
+      "contrast": 0.4,
+      "hue": 0.08,
+      "saturation": 0.5
+    }
+  },
+  "formalize_language": true,
+  "apply_sincos_state_encoding": false,
+  "use_relative_action": true,
+  "use_percentiles": true,
+  "conversation_image_first": false,
+  "max_state_dim": 64,
+  "max_action_dim": 64,
+  "action_horizon": 16,
+  "hidden_size": 1024,
+  "input_embedding_dim": 1536,
+  "general_embodiment_train_ratio": 0.0,
+  "mask_padded_action_dims": true,
+  "add_pos_embed": true,
+  "attn_dropout": 0.0,
+  "use_vlln": false,
+  "max_seq_len": 1024,
+  "n_cog_tokens": 64,
+  "diffusion_model_cfg": {
+    "action_model_max_seq_len": 512,
+    "attention_head_dim": 64,
+    "depth_multi_stream": 4,
+    "depth_single_stream": 8,
+    "dropout": 0.2,
+    "final_dropout": true,
+    "num_attention_heads": 24,
+    "output_dim": 1024,
+    "positional_embeddings": "rope_sa_only",
+    "pre_norm": "layer_norm",
+    "qk_norm": "rms_norm",
+    "rope_theta": 10000.0,
+    "sa_dim": 1536,
+    "temb_type": "input_token",
+    "use_swiglu": true,
+    "vl_dim": 4096
+  },
+  "num_inference_timesteps": 4,
+  "noise_beta_alpha": 1.5,
+  "noise_beta_beta": 1.0,
+  "noise_s": 0.999,
+  "num_timestep_buckets": 1000,
+  "tune_projector": true,
+  "tune_diffusion_model": true,
+  "tune_vlln": true,
+  "action_model_lora": null,
+  "backbone_lora": null,
+  "state_dropout_prob": 0.0,
+  "state_additive_noise_scale": 0.0,
+  "rtc_training_max_delay": 0,
+  "memory": null,
+  "motion": {
+    "insert_layer": 9,
+    "d_hid": 512,
+    "window": [
+      5,
+      9,
+      9
+    ],
+    "ext_chnls": [
+      256
+    ],
+    "int_chnls": [
+      256,
+      256,
+      512
+    ],
+    "corr_func": "cosine",
+    "n_encoders": 1,
+    "use_layerscale": false,
+    "layerscale_init": 1e-05,
+    "use_layernorm": true,
+    "use_syncbn": false,
+    "injection_point": "vision_encoder",
+    "pool_type": "avg",
+    "drop": true,
+    "gradient_check": false
+  },
+  "use_video": true,
+  "video_length": 4,
+  "video_stride": 2,
+  "physics": null,
+  "max_num_embodiments": 8,
+  "format_version": 2
+}

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processor/embodiment_id.json

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processor/processor_config.json

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