Wan 2.2 (Wanxian V2.2) Video LoRA Training Tutorial

Master the refined Wan 2.2 architecture with optimized temporal consistency and native 720p/1080p generation capabilities. This late-2025 tutorial teaches you to inject specific visual styles, character identities, and cinematic motions into the high-fidelity Wanxiang V2.2 video engine.

Product Type: Digital Tutorial (HTML + Markdown)

Why Wan 2.2 over Wan 2.1?
- Reduced morphing artifacts: Significantly improved temporal consistency
- Native 720p/1080p: Higher resolution video generation
- Better camera prompts: Enhanced complex camera movement following
- 7B & 14B Turbo/Pro: Multiple model variants for different use cases
- Spatio-Temporal VAE: New architecture for better video compression

Tutorial Structure (5 Chapters):

【Chapter 1: Hardware & Environment】
- GPU requirements: RTX 4090 (24GB) standard, RTX 5090/A100 optimal
- System RAM: 64GB+ mandatory
- Storage: NVMe Gen 4/5 SSD for high-speed video data
- Software: wan-factory v2.2-dev branch, PyTorch 2.5+, DeepSpeed

【Chapter 2: Dataset Preparation (High-Fidelity)】
- Resolution: 1280x720 (720p) sweet spot, 1920x1080 (1080p) for 40GB+ VRAM
- Clip length: 2-5 seconds, 65 or 81 frame buckets
- Motion quality filtering: Remove blurry footage
- Advanced captioning: Subject-Action-Camera structure
- Spatio-Temporal VAE latent caching with correct VAE version

【Chapter 3: Configuration (YAML)】
- New v2.2 parameters: fps_condition, motion_bucket_id
- FP8 quantization for 14B model on 24GB VRAM
- Network settings: Rank 64, Alpha 32 (half of Rank)
- Learning rate: 2e-5 (lower than Wan 2.1)
- Gradient accumulation: Simulate Batch 4 for stability
- Dynamic bucketing with min/max size settings

【Chapter 4: Training Process】
- Accelerate launch command for v2.2
- Loss curve monitoring (noisy but downward trend)
- Gradient norm monitoring (keep below 1.0)
- Speed estimates: 2.5s/it on RTX 4090 @ 720p
- Total time: ~2.5 hours for 3000 steps

【Chapter 5: Testing (ComfyUI Workflow)】
- Updated WanVideo nodes for v2.2 support
- Dedicated Wan2.2_VAE requirement
- Turbo model settings: 25-30 steps, CFG 5.0-7.0
- LoRA weight ranges: 0.5-0.7 subtle, 0.8-1.0 strong
- Flow Shift parameter for motion intensity control

Bonus: FAQ & Troubleshooting
- Salt and pepper noise fixes (Rank/Alpha adjustment)
- OOM solutions (DeepSpeed, resolution reduction)
- Motion jitter fixes (FPS normalization)
- Color washing fixes (VAE version mismatch)

Technical Requirements:
- NVIDIA GPU with 24GB+ VRAM (32GB+ recommended)
- 64GB+ System RAM
- NVMe Gen 4/5 SSD storage
- Windows/Linux with wan-factory v2.2-dev
- 150GB+ free storage space

Package Contents:
- Wan 2.2 (Wanxian V2.2) Video LoRA Training Tutorial.html (formatted tutorial)
- Wan 2.2 (Wanxian V2.2) Video LoRA Training Tutorial.md (markdown source)

Who This Is For:
- Wan 2.1 users ready to upgrade to higher quality
- Professional video creators needing 720p/1080p outputs
- Cinematic artists seeking reduced morphing artifacts
- Studios requiring temporal consistency in AI videos

Version differences；

Personal Basic Edition: 1 license for course content   Standard customer service consultation support (response within 24 hours on working days)

Personal advanced version: 1 set of course content Authorized priority customer service consultation support (response within 12 hours on working days)

Small Team Edition :1 copy of course content authorization Exclusive customer service for the team (response within 8 hours on working days)