MODEL PROFILE

wan-1.3b-gguf

calcuis · wan-1.3b-gguf

- run it straight with `gguf-connector` - opt a `gguf` file in the current directory to interact with by: > >GGUF file(s) available. Select which one to use: > >1. wan2.1-t2v-1.3b-q4_0.gguf >2. wan2.1-t2v-1.3b-q8_0.gguf >3. wan2.1-vace-1.3b-q4_0.gguf >4. wan2.1-vace-1.3b-q8_0.gguf > >Enter your choice (1 to 4): _ >>> - drag **wan** to > `./ComfyUI/models/diffusion_models` - drag **umt5** to > `./ComfyUI/models/text_encoders` - drag **pig** to > `./ComfyUI/models/vae` - `wan` architecture; should work on both comfyui-gguf and gguf nodes - full set gguf works right away (model + encoder + vae); gguf node is recommended for full gguf - vace model is recommended, since it doesn't need vision clip to work (for i2v and v2v) and run faster than fun model a lot, according to the initial test results - upgrade your node for umt5 gguf encoder support - note: for umt5 gguf, you might encounter oom after rebuilding your tokenizer in the first prompt (once built the tokenizer alive during the session; before you kill it); don't panic, prompt again it should work - base model from wan-ai - comfyui from comfyanonymous - comfyui-gguf city96 (special thanks; fully compatible) - pig architecture from connector - gguf-node (pypi|repo|pack) - gguf-connector (pypi)

Video generationlicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Video
Model weightsNot verified
Profile updated2026/10/31 08:16:31
OVERVIEW

Model overview

- run it straight with `gguf-connector` - opt a `gguf` file in the current directory to interact with by: > >GGUF file(s) available. Select which one to use: > >1. wan2.1-t2v-1.3b-q4_0.gguf >2. wan2.1-t2v-1.3b-q8_0.gguf >3. wan2.1-vace-1.3b-q4_0.gguf >4. wan2.1-vace-1.3b-q8_0.gguf > >Enter your choice (1 to 4): _ >>> - drag **wan** to > `./ComfyUI/models/diffusion_models` - drag **umt5** to > `./ComfyUI/models/text_encoders` - drag **pig** to > `./ComfyUI/models/vae` - `wan` architecture; should work on both comfyui-gguf and gguf nodes - full set gguf works right away (model + encoder + vae); gguf node is recommended for full gguf - vace model is recommended, since it doesn't need vision clip to work (for i2v and v2v) and run faster than fun model a lot, according to the initial test results - upgrade your node for umt5 gguf encoder support - note: for umt5 gguf, you might encounter oom after rebuilding your tokenizer in the first prompt (once built the tokenizer alive during the session; before you kill it); don't panic, prompt again it should work - base model from wan-ai - comfyui from comfyanonymous - comfyui-gguf city96 (special thanks; fully compatible) - pig architecture from connector - gguf-node (pypi|repo|pack) - gguf-connector (pypi)

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。