GLM-5.3 is live. Run Z.ai's latest model on Friendli Model APIs. Try it today ➜
CodeGoat24
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Model Details
Model Provider
CodeGoat24
Model Tree
Qwen/Qwen3.8-27B
Input Modalities
Output Modalities
Supported Functionality
bash
git clone https://github.com/CodeGoat24/WorldRewardcd WorldReward && pip install -e .python examples/run_single_pair.py \--input-image my_data/scene.jpg \--left-video my_data/system_x.mp4 \--right-video my_data/system_y.mp4 \--caption "A sunlit street lined with colorful European-style buildings." \--actions forward,forward,left+camera_down \--frames-per-action 8 \--show-reasoning
Inference needs vLLM new enough to register Qwen3_5ForConditionalGeneration:
bash
python -c "from vllm.model_executor.models.registry import ModelRegistry as R; \print('Qwen3_5ForConditionalGeneration' in R.get_supported_archs())"
bibtex
@article{wang2026worldreward,title={WorldReward: Reward Modeling for Camera-Conditioned World Models},author={Wang, Yibin and Wang, Zehan and Tang, Junshu and Li, Zhimin and Zhou, Yujie and Bu, Jiazi and Ling, Pengyang and Han, Feng and Zhang, Zhixiong and Xing, Long and others},journal={arXiv preprint arXiv:2609.03952},year={2026}}