Wan 2.1 vs. 2.2: A Deep Dive Comparison

A decision-making tool to help you make a strategic choice between two groundbreaking video models.

Core Metrics at a Glance

The following table summarizes the core differences between the two models across key dimensions.

Feature / MetricWan 2.1 (Established)Wan 2.2 (Revolutionary)
Core ArchitectureDiffusion Transformer (DiT)Mixture of Experts (MoE)
Primary StrengthsVACE editing module, mature LoRA ecosystemSuperior raw quality, cinematic camera movement
Hardware Barrier (14B Class)High (Requires ≥16GB VRAM)Similar (MoE architecture optimizes computational cost)
LoRA CompatibilityFully CompatibleIncompatible (Architecture Change)
Temporal ConsistencyGood, but has a recognizable styleExcellent, effectively reduces "AI flicker"
Best Use CasesStylized creation, character consistencyPursuing realism, complex dynamic scenes

Architectural Evolution: From DiT to MoE

The core revolution of Wan 2.2 is the introduction of the Mixture of Experts (MoE) architecture, which fundamentally changes the video generation workflow to break through the performance bottlenecks of a single model.

Wan 2.1: Monolithic Diffusion Transformer (DiT)

Input (Text/Image)
Wan-VAE Encoder (256x Compression)

DiT Core

A single transformer model handles all denoising steps

Wan-VAE Decoder
Output Video

Wan 2.2: Mixture of Experts (MoE)

Input (Text/Image)
VAE Encoder

High-Noise Expert (14B)

Responsible for building macro structure & motion

Switched by SNR guidance

Low-Noise Expert (14B)

Responsible for refining details & temporal coherence

VAE Decoder
Output Video (Higher Quality)

Performance Benchmarks: Cost vs. Efficiency

Hardware requirements are a key factor in determining model usability. The charts below show VRAM usage and generation time on typical hardware.

Peak VRAM Usage

720p Generation Time (Seconds)

The LoRA Compatibility Crisis: A Divided Ecosystem

Wan 2.2's architectural change brings a leap in performance but also breaks compatibility with the 2.1 LoRA ecosystem, forcing users into a difficult strategic choice.

Sticking with Wan 2.1

Vast LoRA Ecosystem: Leverage thousands of community-trained LoRAs for precise character and style control.
VACE Editing Module: Powerful video editing and control capabilities with a mature workflow.
Quality Bottleneck: Raw generation quality and motion fidelity are inferior to 2.2, with a recognizable "AI style".

Embracing Wan 2.2

Superior Raw Quality: A generational leap in realism, detail, and temporal consistency.
Cinematic Camera Movement: More reliable and precise camera motion control.
LoRA Ecosystem Gap: Cannot use LoRAs trained for 2.1, limiting stylization control. Must wait for a new ecosystem to be built.

Strategic Advisor: Which Model is Right for You?

Based on your core needs, we offer the following recommendations.

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If your priority is: Stylization & Character Consistency

When your project heavily relies on a specific artistic style or character consistency, we recommend choosing Wan 2.1. It boasts a vast and mature LoRA ecosystem, which is key to achieving precise visual control. Although the raw quality is slightly lower, its compatibility with community assets is an irreplaceable advantage.

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If your priority is: Ultimate Realism & Camera Movement

When pursuing the ultimate in realism, motion fidelity, and cinematic camera control, we recommend choosing Wan 2.2. Its MoE architecture comprehensively surpasses 2.1 in these areas, making it the undisputed choice for creating highly realistic, complex dynamic scenes and professional-grade camera work.

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If your priority is: Limited Hardware / Non-NVIDIA Platform

For users with limited hardware (e.g., 8-12GB VRAM) or those on non-NVIDIA platforms, we recommend starting with Wan 2.1. Its community support and workflows are relatively more mature, with more available low-VRAM optimization solutions (like quantization). While Wan 2.2 is efficient, its support for non-NVIDIA platforms is still incomplete and more complex to configure.