Workflow GoalProvide a clean, educational reference implementation for WAN 2.2 Text-to-Video generation.This workflow focuses on simplicity, reproducibility, and education rather than including every available feature. It provides a tested baseline for generating high-quality cinematic videos directly from text prompts while remaining easy to understand, modify, and extend.Treat this workflow as a starting point and customize the prompt, LoRA stack, and generation settings for your preferred artistic direction.Version 1.0Purpose✓ Educational✓ Reference Workflow✓ Easy to Understand✓ Easy to Extend✓ Low VRAM FriendlyWorkflow PipelineText Prompt↓Prompt Engineering↓High Noise Sampling↓Low Noise Sampling↓VAE Decode↓(Optional) RIFE Frame Interpolation↓Final Video OutputVerified SettingsThe following settings were used to validate this workflow and are recommended as the baseline configuration.Sampling✓ CFG : 1.0✓ Steps : 6 (3 High Noise + 3 Low Noise)✓ Shift : 10✓ Sampler : Euler✓ Scheduler : SimpleVideo✓ Frames : 81✓ Output FPS : 16 FPS✓ Final FPS (RIFE Enabled) : 32 FPS✓ Recommended Resolution : 640 × 360 (16:9)Required LoRA ConfigurationThis workflow uses the same Lightx2V LoRA during both sampling stages.LoRAlightx2v_t2v_14b_cfg_step_distill_v2_lora_rank32_bf16High NoiseStrength : 2.0Low NoiseStrength : 1.0These strengths were used to validate the workflow and are recommended as the baseline configuration.Optional Post ProcessingThe workflow includes an optional RIFE Frame Interpolation stage.When enabled:Input : 16 FPSOutput : 32 FPSProduces smoother motion while preserving the original video duration.Disable this stage if you prefer faster processing or do not have the required RIFE model installed.Hardware &amp; Resolution NotesValidated using:✓ NVIDIA RTX 2080 (8 GB VRAM)✓ 64 GB System RAM✓ ComfyUI v0.27+Although optimized for 8 GB VRAM, WAN 2.2 Text-to-Video remains computationally intensive.System RAM is equally important for handling intermediate tensors and memory paging during video generation.Expected behavior:8 GB VRAM + 16 GB RAMPossible out-of-memory errorsSlower generation8 GB VRAM + 32 GB RAMBetter stabilityPerformance depends on available system memory8 GB VRAM + 64 GB RAM (or more)Recommended configurationMatches the environment used to validate this workflowDesign PhilosophyThis workflow intentionally avoids unnecessary complexity.The objective is to provide a stable, reproducible reference implementation that users can understand, learn from, and extend for their own creative projects.Features✓ Clean reference implementation✓ Prompt Engineering ready✓ High / Low Noise sampling pipeline✓ Modular LoRA configuration✓ Optional RIFE interpolation (16 → 32 FPS)✓ Chrono Save integration for CivitAI✓ Low VRAM focused workflow design

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