MODEL PROFILE · 模型档案

Hy-Nomas

腾讯 · Hy-Nomas

**Hy-Nomas** is a video world generation model that supports free-form, multi-turn interaction through text instructions and camera control. It generates a world one video segment at a time, allowing users to introduce objects, change styles and scenes, describe actions, or control the camera as generation continues. The model combines a segment-wise autoregressive diffusion transformer (DiT), a Qwen text encoder, camera-conditioning modules, and a PixelUMM video decoder. A persistent key/value (KV) cache carries context between segments. The distilled inference configuration uses **8 denoising steps**, with **720 × 1280** output at **24 FPS**. A separate configuration supports video generation on a **single NVIDIA GeForce RTX 4090** using INT8 DiT weights, an INT8 KV cache, an FP8 decoder, and CPU offload. - **Free-form interaction:** Guide successive segments with instructions about subjects, actions, appearance, style, and environment. - **Camera control:** Supply camera trajectories alongside text to control viewpoint and movement. - **Continuous generation:** Reuse earlier context through a KV cache when extending the same world. - **Distilled inference:** Generate each segment with 8 DiT denoising steps and decode its latents with a fine-tuned PixelUMM decoder. - **Flexible deployment:** Use the standard sequence-parallel configuration or the single-GPU configuration, and interact through the web demo.

译文排队中,当前展示来源原文。

license:apache-2.0
上下文窗口来源未披露
输入 → 输出待核验 → 待核验
模型权重待核验
档案更新时间2026/10/31 03:08:28
OVERVIEW

模型介绍

**Hy-Nomas** is a video world generation model that supports free-form, multi-turn interaction through text instructions and camera control. It generates a world one video segment at a time, allowing users to introduce objects, change styles and scenes, describe actions, or control the camera as generation continues. The model combines a segment-wise autoregressive diffusion transformer (DiT), a Qwen text encoder, camera-conditioning modules, and a PixelUMM video decoder. A persistent key/value (KV) cache carries context between segments. The distilled inference configuration uses **8 denoising steps**, with **720 × 1280** output at **24 FPS**. A separate configuration supports video generation on a **single NVIDIA GeForce RTX 4090** using INT8 DiT weights, an INT8 KV cache, an FP8 decoder, and CPU offload. - **Free-form interaction:** Guide successive segments with instructions about subjects, actions, appearance, style, and environment. - **Camera control:** Supply camera trajectories alongside text to control viewpoint and movement. - **Continuous generation:** Reuse earlier context through a KV cache when extending the same world. - **Distilled inference:** Generate each segment with 8 DiT denoising steps and decode its latents with a fine-tuned PixelUMM decoder. - **Flexible deployment:** Use the standard sequence-parallel configuration or the single-GPU configuration, and interact through the web demo.

主要特点

特点摘要待依据来源补齐,不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价,不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价,请查阅来源渠道。

按月估算基础 Token 费用

—

预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用?

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗?

不是实时结算价格,而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。