MODEL PROFILE

lingbot-video-moe-30b-a3b

robbyant · lingbot-video-moe-30b-a3b

We are excited to introduce **LingBot-Video**, the first open-source large-scale MoE (Mixture-of-Experts) video generation model dedicated to embodied intelligence. As a top-tier video model, LingBot-Video is designed to bridge the gap between video synthesis and physical world understanding. > **💡 Rewriter deployment**: the bundled rewriter uses the single-process > `transformers` backend. For higher throughput, deploy the VLM yourself and call > it through an OpenAI-compatible API. Preserve the two-stage semantics: step 1 > must use the base VLM without the rewriter LoRA, while step 2 must use the same > base VLM with the rewriter LoRA enabled. This can be implemented with two > endpoints, or with one server that can select the adapter per request. See > vLLM / SGLang official docs. Install the optional SGLang dependencies only when using SGLang Diffusion or the fused / FP8 MoE runtime:

license:apache-2.0
Context windowNot disclosed
Input → Output待核验 → 待核验
Model weightsNot verified
Profile updated2026/10/30 02:11:54
OVERVIEW

Model overview

We are excited to introduce **LingBot-Video**, the first open-source large-scale MoE (Mixture-of-Experts) video generation model dedicated to embodied intelligence. As a top-tier video model, LingBot-Video is designed to bridge the gap between video synthesis and physical world understanding. > **💡 Rewriter deployment**: the bundled rewriter uses the single-process > `transformers` backend. For higher throughput, deploy the VLM yourself and call > it through an OpenAI-compatible API. Preserve the two-stage semantics: step 1 > must use the base VLM without the rewriter LoRA, while step 2 must use the same > base VLM with the rewriter LoRA enabled. This can be implemented with two > endpoints, or with one server that can select the adapter per request. See > vLLM / SGLang official docs. Install the optional SGLang dependencies only when using SGLang Diffusion or the fused / FP8 MoE runtime:

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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。

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Frequently asked questions

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Sources & traceability

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。