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DreamX-World-5B

GD-ML

**DreamX-World** is a general-purpose world model for **interactive world simulation**. It generates diverse, high-fidelity worlds that users can explore, control, and transform with event prompts. **DreamX-World-5B** is the long-horizon autoregressive variant of DreamX-World. It is built on top of Wan2.2-TI2V-5B and generates videos from an input image, a text prompt, and keyboard-style camera action commands. Compared with the 5B-Cam variant, DreamX-World-5B uses chunk-wise causal autoregressive inference with KV caching, making long-horizon generation practical, including videos up to about 1 minute at 16 FPS. The model is trained with a scalable data engine on Unreal Engine data, gameplay footage, and real-world videos, together with camera estimation and data filtering. DreamX-World follows a progressive training pipeline for action control, open-ended event response, reinforcement-learning-based action following, and efficient inference through forcing and distillation.

Video generation

Input Image→ Output Video

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DreamX-World-5B-Cam

GD-ML

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Video generation

Input Image→ Output Video

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Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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How should API prices be compared?+

Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

Do open weights mean free commercial use?+

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Is the top-ranked model the best for me?+

Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.