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vllm-omni-wan2.2-t2v
Wan2.2-T2V-A14B via vLLM-Omni - Text-to-video generation model from Wan-AI. Generates high-quality videos from text prompts using a 14B parameter diffusion model.

Repository: localaiLicense: apache-2.0

vllm-omni-wan2.2-i2v
Wan2.2-I2V-A14B via vLLM-Omni - Image-to-video generation model from Wan-AI. Generates high-quality videos from images using a 14B parameter diffusion model.

Repository: localaiLicense: apache-2.0

ltx-2
**LTX-2** is a DiT-based audio-video foundation model designed to generate synchronized video and audio within a single model. It brings together the core building blocks of modern video generation, with open weights and a focus on practical, local execution. **Key Features:** - **Joint Audio-Video Generation**: Generates synchronized video and audio in a single model - **Image-to-Video**: Converts static images into dynamic videos with matching audio - **High Quality**: Produces realistic video with natural motion and synchronized audio - **Open Weights**: Available under the LTX-2 Community License Agreement **Model Details:** - **Model Type**: Diffusion-based audio-video foundation model - **Architecture**: DiT (Diffusion Transformer) based - **Developed by**: Lightricks - **Paper**: [LTX-2: Efficient Joint Audio-Visual Foundation Model](https://arxiv.org/abs/2601.03233) **Usage Tips:** - Width & height settings must be divisible by 32 - Frame count must be divisible by 8 + 1 (e.g., 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97, 105, 113, 121) - Recommended settings: width=768, height=512, num_frames=121, frame_rate=24.0 - For best results, use detailed prompts describing motion and scene dynamics **Limitations:** - This model is not intended or able to provide factual information - Prompt following is heavily influenced by the prompting-style - When generating audio without speech, the audio may be of lower quality **Citation:** ```bibtex @article{hacohen2025ltx2, title={LTX-2: Efficient Joint Audio-Visual Foundation Model}, author={HaCohen, Yoav and Brazowski, Benny and Chiprut, Nisan and others}, journal={arXiv preprint arXiv:2601.03233}, year={2025} } ```

Repository: localaiLicense: ltx-2-community-license-agreement

wan-2.1-i2v-14b-480p-ggml
Wan 2.1 I2V 14B 480P — image-to-video diffusion, GGUF Q4 quantization. Animates a reference image into a 33-frame 480p clip. Requires more RAM than the 1.3B T2V variant; CPU offload enabled by default.

Repository: localaiLicense: apache-2.0

wan-2.1-flf2v-14b-720p-ggml
Wan 2.1 FLF2V 14B 720P — first-last-frame-to-video diffusion, GGUF Q4_K_M. Takes a start and end reference image and interpolates a 33-frame clip between them. Unlike the plain I2V variant this model feeds the end frame through clip_vision as well, so it conditions semantically (not just in pixel-space) on both endpoints. That makes it the right choice for seamless loops (start_image == end_image) and clean narrative cuts. Native 720p but accepts 480p resolutions; shares the same VAE, t5xxl text encoder, and clip_vision_h as I2V 14B.

Repository: localaiLicense: apache-2.0

ltx-2.3
**LTX-2.3** is an improved DiT-based audio-video foundation model from Lightricks, building upon the LTX-2 architecture with enhanced capabilities for generating synchronized video and audio within a single model. **Key Features:** - **Joint Audio-Video Generation**: Generates synchronized video and audio in a single model - **Image-to-Video**: Converts static images into dynamic videos with matching audio - **Enhanced Quality**: Improved video quality and motion generation over LTX-2 - **Open Weights**: Available under the LTX-2 Community License Agreement **Model Details:** - **Model Type**: Diffusion-based audio-video foundation model - **Architecture**: DiT (Diffusion Transformer) based - **Developed by**: Lightricks - **Parent Model**: LTX-2 **Usage Tips:** - Width & height settings must be divisible by 32 - Frame count must be divisible by 8 + 1 (e.g., 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97, 105, 113, 121) - Recommended settings: width=768, height=512, num_frames=121, frame_rate=24.0 - For best results, use detailed prompts describing motion and scene dynamics **Limitations:** - This model is not intended or able to provide factual information - Prompt following is heavily influenced by the prompting-style - When generating audio without speech, the audio may be of lower quality

Repository: localaiLicense: ltx-2-community-license-agreement