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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-2.3-22b-dev-ggml
LTX-2.3 22B dev - DiT-based audio-video foundation model from Lightricks, GGUF-quantized for the stable-diffusion.cpp backend. Generates synchronized video and audio from a text prompt (T2V), a reference image (I2V), or first/last frame pairs (FLF2V). Uses gemma-3-12b-it as the text encoder and ships dedicated video and audio VAEs plus an embeddings_connectors safetensors that bridges the LLM hidden states to the diffusion model. This entry uses the dynamic (UD) Q4_K_M quantization of the 22B model (~16 GB) paired with the UD-Q4_K_XL QAT Gemma encoder (~7.4 GB). Recommended generation: width=1280, height=720, video_frames=33, fps=24, sampler=euler, cfg_scale=6.0.

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

ltx-2.3-22b-dev-ggml-q4_k_m
LTX-2.3 22B dev - non-dynamic Q4_K_M quantization (~14.3 GB). Same pipeline as ltx-2.3-22b-dev-ggml but with the plain Q4_K_M weights instead of the dynamic UD-Q4_K_M variant. Slightly smaller and slightly lower quality.

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

ltx-2.3-22b-dev-ggml-q8_0
LTX-2.3 22B dev - Q8_0 quantization (~22.8 GB). Highest-quality quantized dev variant on the cpp backend; needs roughly twice the VRAM/RAM of the Q4 entries but produces noticeably cleaner audio and motion. Paired with the QAT Gemma-3 12B encoder.

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

ltx-2.3-22b-distilled-ggml
LTX-2.3 22B distilled - faster student of the dev model, GGUF-quantized for the stable-diffusion.cpp backend. Trades a small amount of quality for substantially fewer sampling steps, making it the right pick for iterative previews and CPU-offloaded inference. Same input modalities as the dev entry (T2V / I2V / FLF2V) and the same gemma-3-12b-it text encoder. This entry uses the dynamic (UD) Q4_K_M quantization of the 22B distilled model (~16.3 GB). Recommended generation: width=1280, height=720, video_frames=33, fps=24, sampler=euler, cfg_scale=6.0.

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

ltx-2.3-22b-distilled-ggml-q4_k_m
LTX-2.3 22B distilled - non-dynamic Q4_K_M quantization (~14.3 GB). Same pipeline as ltx-2.3-22b-distilled-ggml but with the plain Q4_K_M weights instead of the dynamic UD-Q4_K_M variant.

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

ltx-2.3-22b-distilled-ggml-q8_0
LTX-2.3 22B distilled - Q8_0 quantization (~22.8 GB). Highest-quality distilled variant on the cpp backend; useful when you want the distilled sampling cost but the cleanest possible output.

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