━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎬 **LTX-2.3 Image-to-Video Workflow** QwenVL Auto-Prompt · No Drift · ComfyUI ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Pure LTX 2.3 22B image-to-video pipeline for ComfyUI. Drop an image, get professional motion. QwenVL vision model automatically analyzes your input image and generates a motion-aware prompt—no manual description needed. The workflow enforces locked static camera (anti-drift), scales dynamically to any input resolution, and upscales output to broadcast-quality 1920×1088 at 24 FPS. Production-ready for stock footage, ambient loops, and commercial video generation. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✨ **Features** ✅ QwenVL Auto Motion Director — Vision model reads input image → auto-generates motion prompt with camera lock and object tracking hints ✅ Locked Static Camera — Zero pan, zoom, or drift; all motion in-frame only ✅ Pure LTX 2.3 22B — No LoRA needed; GGUF quantization for 16GB VRAM ✅ Dynamic Pixel Scaling — Auto-scales any input size to optimal 0.52MP for 8-step inference ✅ Dual-Stage Upscale — 960×544 base → 2× spatial upscaler → 1920×1088 output ✅ Audio + Video VAE — Multi-modal encoding; ready for synced audio pipelines ✅ 24 FPS Native — Smooth playback; 168 frames per generation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📦 **Required Models** (6 files, ~32 GB) • ltx-2.3-22b-distilled-Q4_K_M.gguf (17.8 GB) — Main UNet diffusion model (GGUF Q4 quantized) • gemma_3_12B_it_fp4_mixed.safetensors (9.45 GB) — Text encoder for LTX prompt understanding • ltx-2.3_text_projection_bf16.safetensors (2.31 GB) — Text-to-latent projection layer • LTX23_video_vae_bf16.safetensors (1.45 GB) — Video VAE codec (encode/decode video frames) • LTX23_audio_vae_bf16.safetensors (365 MB) — Audio VAE codec (dual-modal support) • ltx-2.3-spatial-upscaler-x2-1.1.safetensors (996 MB) — 2× spatial upscaler for final quality pass ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⬇️ **Download Links** (verified HuggingFace) 📁 **ComfyUI/models/unet/** • LTX-2.3-22B-distilled-1.1-Q4_K_M.gguf (17.8 GB) — https://huggingface.co/QuantStack/LTX-2.3-GGUF 📁 **ComfyUI/models/text_encoders/** • gemma_3_12B_it_fp4_mixed.safetensors (9.45 GB) — https://huggingface.co/Comfy-Org/ltx-2 • ltx-2.3_text_projection_bf16.safetensors (2.31 GB) — https://huggingface.co/Kijai/LTX2.3_comfy 📁 **ComfyUI/models/vae/** • LTX23_video_vae_bf16.safetensors (1.45 GB) — https://huggingface.co/Kijai/LTX2.3_comfy • LTX23_audio_vae_bf16.safetensors (365 MB) — https://huggingface.co/Kijai/LTX2.3_comfy 📁 **ComfyUI/models/upscale_models/** • ltx-2.3-spatial-upscaler-x2-1.1.safetensors (996 MB) — https://huggingface.co/Lightricks/LTX-2.3 ⚠️ *VAE files are NOT in the official Lightricks repo — get them from Kijai/LTX2.3_comfy. Gemma fp4 encoder hosted by Comfy-Org. Filenames use v1.1 (current stable hotfix release).* ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🧩 **Required Custom Nodes** • LTXV — Lightricks LTX-Video extension (sampling, encoding, projection) • AILab_QwenVL_Advanced — QwenVL vision model integration for image-to-text • ComfyUI-GGUF — UnetLoaderGGUF for quantized model loading • VideoHelperSuite — VHS_VideoCombine, frame batching, video output export • rgthree-comfy — Fast Groups Bypasser (optional; used for workflow flexibility) • ImageIterator — Batch image loader for multi-image workflows • ImageScaleToTotalPixels — Dynamic resolution scaling to pixel budget • GetImageSize+ — Image dimension detection for auto-scaling pipeline ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 **How to Use** 1. Place your input image(s) in the ComfyUI ./input directory 2. Load this workflow into ComfyUI 3. (Optional) Review the auto-generated motion prompt in the QwenVL output text node 4. Queue and generate 5. Output video saved via VHS to ./output directory The entire motion prompt generation and scaling pipeline runs automatically—queue once, get your result. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ **Settings & Parameters** • FPS — 24 (Standard frame rate; 168 total frames per generation) • Pixel Budget — 0.52 MP (Optimal for 8-step sampling on 16GB VRAM) • Sampler — er_sde (Low-drift SDE solver for stable motion) • Base Steps — 8 (Main diffusion sampling passes) • Refine Steps — 3 (Quality refinement after upscale) • CFG Scale — 1.0 (Classifier-free guidance; 1.0 = no guidance, stable output) • Output Resolution — 1920×1088 (After 2× spatial upscale) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 **Performance Tips** • Batch Multiple Images — Queue 5–10 images in one session to amortize model load time • Input Image Quality — Sharp, well-lit images yield sharper motion; low-contrast images may produce soft motion • Motion Prompt Tuning — Edit the QwenVL text output node before queuing if you want specific motion direction (e.g., remove camera keywords to force static) • Speed vs. Quality — The dual-stage upscale adds ~20 seconds per clip. Bypass the Spatial Upscaler node if speed is critical (output at 960×544) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📝 **Notes & AI Disclosure** • AI-Generated Content — All example outputs are AI-generated by LTX 2.3. Suitable for stock footage, ambient loops, and creative projects. • Model Downloads — See the "Download Links" section above for exact HuggingFace repos and target folders. • Hardware Tested — RTX 5080 16GB VRAM; CUDA compute 9.2+ • VRAM Usage — ~14 GB peak during sampling; requires fast SSD for frame buffering • No Commercial Guarantees — Use at your own discretion. Respect local AI disclosure laws when publishing outputs. Enjoy clean, drift-free motion generation. Questions? Test the workflow locally first—Civitai comments section is for feedback, not troubleshooting. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔗 **Also check out** New: **[SeedVR2 Batch Upscaler](https://civitai.red/models/2750373/seedvr2-batch-upscaler-sleep-on-it-wake-up-4k?modelVersionId=3094090)** — Sleep On It, Wake Up 4K. Drop a whole folder of stills, walk away, come back to 4K. Great for upscaling your generations. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⭐ **Found this useful?** • Like if it saved you time • Comment your results — I read every one • Follow for new ComfyUI workflows, all tested on 16 GB VRAM ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚖️ **Model Attribution & Licensing** **LTX-Video 2.3** (Lightricks) • License: LTX-2 Community License — https://huggingface.co/Lightricks/LTX-2.3/blob/main/LICENSE • Free for commercial use by entities under $10M USD annual revenue • AI-generated content disclosure required **Gemma 3 12B IT** (Google DeepMind) • License: Gemma Terms of Use — https://ai.google.dev/gemma/terms • Subject to Google's Prohibited Use Policy **Custom Nodes** • LTXV (Lightricks), VideoHelperSuite (MIT), AILab QwenVL, rgthree-comfy (MIT), ComfyUI-GGUF All example outputs are AI-generated. This workflow (JSON configuration) is shared as original work; model weights must be downloaded separately from the official sources above.
