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Wan 2.1

by Alibaba
  • What it is:Wan 2.1 is an open-source video generation model from Qwen (wan.video) using diffusion transformer and Wan-VAE technology for SOTA text-to-video, image-to-video, and editing at up to 1080p on consumer GPUs.
  • Best for:Open-source AI enthusiasts and developers, Game studios and indie creators, Content creators needing quick prototypes
  • Pricing:Free tier available, paid plans from $0.22 per generation
  • Rating:85/100Very Good
  • Expert's conclusion:Wan 2.1 provides the best of breed, open-source video generation technology for technically savvy users that value quality, affordability, and accessibility over user-friendliness.
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Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Are Wan 2.1's Key Business Metrics?

📊
1.3B (T2V model)
Parameters
📊
8.19GB
VRAM Requirement
📊
5-15 seconds
Max Video Length
📊
1080p
Max Resolution
📊
SOTA open-source performance
Benchmarks

How Credible and Trustworthy Is Wan 2.1?

85/100
Excellent

The Wan model (open-source) has a slightly different target audience compared to Kling (closed-source).

BREAKDOWN
Product Maturity88/100
Company Stability95/100
Security & Compliance70/100
User Reviews82/100
Transparency92/100
Support Quality75/100
TRUST SIGNALS
Developed by Alibaba Tongyi Lab/QwenOpen source with GitHub availabilitySOTA benchmark performanceRuns on consumer GPUs (8.19GB VRAM)

What Are the Key Features of Wan 2.1?

✨
Text-to-Video Generation
The Wan model has a larger target audience in both game developers and content creators that want to create video content from text or images.
💬
Image-to-Video Support
Compared to Kling, Wan has an advantage when it comes to speed and motion smoothness (approximately 2.5x faster than Kling's use of a 3D Causal VAE).
✨
Consumer GPU Compatibility
Wan can only generate longer video content than Kling by about 50%.
✨
Video VAE (Wan-VAE)
Wan is only able to produce content with lengths ranging from 6 seconds to 15 seconds.
📊
Readable Text Generation
Kling may be able to produce much longer content.
📊
Advanced Motion Control
Wan is an open source model.
✨
Open Source Architecture
Wan has a lower barrier to entry than Kling.

What Are the Best Use Cases for Wan 2.1?

AI Developers & Researchers
Kling is a closed-source model that is only available on platforms such as Layer.
Content Creators & Animators
Kling has significantly more market presence than Wan.
Social Media Video Producers
Kling has a larger client base in the area of creating higher-end video generation.
Educational Video Creators
https://www.openaccessgovernment.org/wan-21-a-text-image-to-video-model-for-game-and-content-development/
NOT FORFeature Film Production
https://arxiv.org/abs/2303.13693
NOT FORReal-time Live Streaming
https://github.com/qwen-team/WAN-2.1

How Much Does Wan 2.1 Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
Open Source ModelFreeDownload and run locally on consumer GPUs (8.19GB+ VRAM required)—
Eachlabs Playground$0.22 per generationBrowser-based access, $1 credits ~4 generationsEachlabs
Wan AI PlatformFreeOnline generator with text-to-video including scripts, subtitles, musicwan.video
Promptus.ai ComfyUIFreeBrowser-based workflow interface for local model executionPromptus.ai
Open Source ModelFree
Download and run locally on consumer GPUs (8.19GB+ VRAM required)
Eachlabs Playground$0.22 per generation
Browser-based access, $1 credits ~4 generations
Eachlabs
Wan AI PlatformFree
Online generator with text-to-video including scripts, subtitles, music
wan.video
Promptus.ai ComfyUIFree
Browser-based workflow interface for local model execution
Promptus.ai

How Does Wan 2.1 Compare to Competitors?

FeatureWan 2.1Google VO2Cling 1.6 ProMinimax
Text-to-VideoYesYesYesYes
Image-to-VideoYes
Readable Text in VideoYes (EN/CN)NoNoNo
Max Resolution1080p
VRAM Requirement8.19GBHigh-endHigh-endHigh-end
Open SourceYesNoNoNo
Fight Scene PhysicsExcellentPoorPoorPoor
Consumer GPU SupportYesNoNoNo
CostFree (open source)CommercialCommercialCommercial
Benchmark PerformanceSOTALagsLagsLags
Text-to-Video
Wan 2.1Yes
Google VO2Yes
Cling 1.6 ProYes
MinimaxYes
Image-to-Video
Wan 2.1Yes
Google VO2—
Cling 1.6 Pro—
Minimax—
Readable Text in Video
Wan 2.1Yes (EN/CN)
Google VO2No
Cling 1.6 ProNo
MinimaxNo
Max Resolution
Wan 2.11080p
Google VO2—
Cling 1.6 Pro—
Minimax—
VRAM Requirement
Wan 2.18.19GB
Google VO2High-end
Cling 1.6 ProHigh-end
MinimaxHigh-end
Open Source
Wan 2.1Yes
Google VO2No
Cling 1.6 ProNo
MinimaxNo
Fight Scene Physics
Wan 2.1Excellent
Google VO2Poor
Cling 1.6 ProPoor
MinimaxPoor
Consumer GPU Support
Wan 2.1Yes
Google VO2No
Cling 1.6 ProNo
MinimaxNo
Cost
Wan 2.1Free (open source)
Google VO2Commercial
Cling 1.6 ProCommercial
MinimaxCommercial
Benchmark Performance
Wan 2.1SOTA
Google VO2Lags
Cling 1.6 ProLags
MinimaxLags

How Does Wan 2.1 Compare to Competitors?

vs Kling 1.6 Pro

https://tongyilab.github.io/Kling/

Wan 2.1 is best suited for rapid prototyping and workflow-based applications focused on efficiency; Kling is better suited for high end production requirements.

vs Hunyuan

XYZEO Analysis: Both are part of the AI video generation marketplace. Wan 2.1 outperformed Hunyuan in terms of motion smoothness, scene consistency, and spatial accuracy based upon the benchmark tests. Wan uses large-scale training data (1.5 B videos, 10 B images), which will produce output that looks much more natural than Hunyuan does. Hunyuan has a larger ecosystem that it can be used on, including Layer. The source code for Wan is entirely open-sourced (and therefore budget friendly), whereas the source code for Hunyuan may need to be purchased and/or licensed; as such Wan currently enjoys greater momentum because it is the most recently released open model outperforming Hunyuan.

Choose Wan 2.1 if you want to take advantage of cutting edge open-source quality; choose Hunyuan if you are looking for established ecosystems on platforms.

vs Veo 2

XYZEO Analysis: Premium vs. open-source positioning – Veo 2 (Google) is positioned towards enterprise level content creators who have high levels of feature adoption through its enterprise version, while Wan 2.1 is targeted at independent developers and rapid prototyping with lower memory usage and faster generation times. Although both models support generating video from text or image inputs, they do not offer identical features; Veo supports greater scale and polish than Wan. However, as a result of Veo's higher price point, Wan is gaining momentum in the market as an open-source alternative to Veo.

Choose Wan 2.1 if you are seeking cost effective, customizable video generation; choose Veo 2 if you are looking for professional grade reliability.

vs Minimax

XYZEO Analysis: Competitors in the open AI video generation space on platforms such as Layer. Wan 2.1 outperforms Minimax in terms of efficiency, consistency, and amount of training data, resulting in smoother motion. Minimax provides live capabilities, however, it falls behind Wan in terms of spatial accuracy. Both are priced competitively and in the middle-of-the-road in terms of cost in the open-source space; Wan is gaining momentum as the leading open model.

Wan 2.1 prioritizes quality and speed in its video generation applications over live features.

What are the strengths and limitations of Wan 2.1?

Pros

  • Motion smoothness superior to other open-source competitors like Hunyuan due to advanced DiT and VAE architecture.
  • Fastest generation time among open-source competitors — generates 2.5X faster than prior reconstruction methods with low memory usage ideal for iteration.
  • Large-scale training data — yields natural, fluid video outputs by leveraging 1.5B videos and 10B images.
  • Open-source and free — no cost barriers to entry and can be customized for use within the global community.
  • Flexible Inputs — Supports both Text-to-Video up to 800 characters and Image-to-Video with Auto Aspect Ratio
  • High-Quality Short Clips — 1080p HD up to 15 seconds with Style Palettes like Anime and 3D Cartoon
  • Great Consistency — Sharp Details for Game Assets, Cinematics, Realistic Scenes

Cons

  • Short Video Length — Limited to 6–15 seconds even at lower resolutions
  • Resource Intensive — Requires Powerful GPU, Slow Performance on Consumer Hardware, e.g., 8 minutes for 3 second clip
  • Technical Complexity in Local Setup — Comfy UI Workflows Require Technical Expertise in Creating Prompts, Samplers, Upscaling
  • Default Frame Rate Lower Than Expected — 16 FPS Needs Interpolation for Smooth Motion
  • No Native Audio Synchronization in Base — Website Mentions This, but Core Model Focuses Primarily on Visuals
  • Quirks with Chinese Models — Potential Negative Prompt Issues, Less Optimized for Content Produced in the West
  • No Cloud-Based Free Tier — Only Run Locally, Lack Easy Hosted Access Such as Competitors Offer

Who Is Wan 2.1 Best For?

Best For

  • Open-source AI enthusiasts and developers — Customizable Model Free and Integrated with Comfy UI for Full Control Over Workflows
  • Game studios and indie creators — Fast Memory Usage and Perfect for Cinematics, Animations, and Asset Prototyping on Layer
  • Content creators needing quick prototypes — Rapidly Generate Text/Image to Video for Social Media Clips, Ads, Storyboards with Many Styles
  • Teams with strong GPU hardware — Uses Local Processing to Produce High-Quality Outputs Without Subscription Costs
  • Researchers benchmarking video models — Provides Much Better Output Results in Motion/Scene Metrics than Peers; Large Dataset for Study

Not Suitable For

  • Beginners without technical skills — Requires Technical Setup/Prompting with Comfy UI; Consider Using Hosted Tools Such as Kling on Layer Instead
  • Users needing long-form videos (>15s) — Has Very Strict Length Limits; Consider Using Kling 1.6 Pro or Veo 2 for Longer Narratives
  • Low-spec hardware owners — Can Cause Failures and/or Slow Down Due to GPU Strain; Use Cloud Platforms Such as CapCut Wan Integration
  • Real-time video production teams — Too Slow for Live Applications; Optimize for Minimax Live

Are There Usage Limits or Geographic Restrictions for Wan 2.1?

Video Duration
6-15 seconds maximum (1080p HD)
Frame Rate
30 FPS supported, defaults to 16 FPS in local setups
Text Prompt Length
Maximum 800 characters
Resolution
1080p HD; lower for longer clips
Aspect Ratios
16:9, 9:16, 1:1, 4:3, 3:4; auto for images
Input Images
1-2 reference images for image-to-video
Hardware Requirement
High-end GPU required for local runs
Geographic Availability
Open-source: global download; some platforms may restrict China-origin models
Compliance
Open-source license (Apache/MIT assumed); check for commercial use restrictions

What APIs and Integrations Does Wan 2.1 Support?

API Type
No official REST/GraphQL API; open-source model for local inference via ComfyUI/ diffusion pipelines
Authentication
N/A for open-source; platform-specific (e.g., Layer.ai API keys)
Webhooks
Not supported natively; platform-dependent
SDKs
Python diffusion libraries (Diffusers), ComfyUI nodes; community implementations
Documentation
GitHub repos, ComfyUI workflows, tutorials on YouTube/ThinkDiffusion; model cards detail architecture
Sandbox
Local testing via ComfyUI; hosted on Layer.ai, CapCut for no-setup trials
SLA
None (open-source); platform SLAs apply (e.g., Layer.ai uptime)
Rate Limits
Hardware-dependent locally; platform quotas (e.g., CapCut generations)
Use Cases
Text-to-video, image-to-video via custom pipelines; integrate in game engines, creative apps

What Are Common Questions About Wan 2.1?

Wan 2.1 is Alibaba's Open-Source AI Video Generation Model Focused on Generating Smooth 6–15 Second 1080p HD Clips with Realistic Motion Through The Use of 3D Variational Autoencoder and Deep Iterative Training Architecture

Hugging face download with Comfy UI workflows for your local GPU inference. The tutorials go over how to set up a prompt, different samplers and upscaling. Also hosted versions are available through Layer.ai and Cap Cut.

In terms of speed (2.5 x faster) motion (smoother) and consistency, open source Wan 2.1 performs better than all other options reviewed. While Kling will allow longer videos (Hunyuan allows for longer videos due to platform integration), it does lag behind in quality metrics.

As much as 15 seconds at 1080p depending on what settings you choose. Shorter time at higher settings. To get longer output times reduce resolution, frames, etc., then upscale.

Yes, Wan 2.1 is fully open source and you can use it for personal or commercial purposes (just check the licensing).

If you want to run the generation of Wan 2.1 using a high end GPU (such as an RTX 40 series) the generation time per clip can be minutes long. Run lower setting if running on less powerful hardware.

The core visual generation model does generate video visuals; however, wan.video states they are working on native synced audio in HD narrative mode, but this would need to be done separately when running a local version of Wan 2.1.

Because Wan 2.1 is an open source model you can generate video locally which keeps your video private. Anytime you upload your video to a hosting site (such as Layer), those sites have their own policies regarding data usage; there is no cloud training on user generated content.

Is Wan 2.1 Worth It?

Wan 2.1 is a free, open source video generation model developed by Qwen. It is able to produce very high quality 1080p videos from both text and image inputs, with significantly improved motion quality and bilingual text input support (English & Chinese), and can run efficiently on most consumers level hardware. It also outperformed all other alternatives (both open source and commercial) in testing, although to achieve the highest quality video possible, users would have to stitch together short clips of video to create longer videos. XYZEO Analysis.

Recommended For

  • For individual creators and hobbyist's that wish to create high quality videos using free AI video generation tools
  • For developers that wish to experiment with free, open source AI video models using consumer level GPUs
  • For content creators that need to include bilingual text in their videos (English & Chinese)
  • For teams that prioritize deploying video generation models locally to protect privacy and save money on cloud services

!
Use With Caution

  • For users that want to generate videos that are longer than 5-15 seconds without having to do additional post production work to "stitch" together multiple video clips
  • For beginners who are new to using Comfy UI or Diffusion Model Workflows
  • Developers and organizations utilizing GPUs less than 12 GB VRAM for the 14 B model.
  • Any applications which require generating video in real time or have a need for large-scale throughput for production.

Not Recommended For

  • Anyone looking for a completely hosted, SaaS solution without having to deal with setting up their own infrastructure.
  • Organizations' commercial teams that may require enterprise level support, Service Level Agreements (SLA), and/or customization options/services.
  • Enterprises that are budget conscious but still want a polished, ready to deploy platform.
  • Casual users expecting to be able to create video with just one click without having to learn anything.
Expert's Conclusion

Wan 2.1 provides the best of breed, open-source video generation technology for technically savvy users that value quality, affordability, and accessibility over user-friendliness.

Best For
For individual creators and hobbyist's that wish to create high quality videos using free AI video generation toolsFor developers that wish to experiment with free, open source AI video models using consumer level GPUsFor content creators that need to include bilingual text in their videos (English & Chinese)

What do expert reviews and research say about Wan 2.1?

Key Findings

Wan 2.1 is Qwen's open-source video generation model (1.3B & 14B parameters) that is the leading benchmark in motion quality, visual fidelity, and bilingual text generation; while it can run efficiently on consumer-grade hardware using the diffusion transformer and Wan-VAE architectures. It supports: text-to-video, image-to-video, inspiration mode, and sound effects, and is available as a complimentary download and includes ComfyUI integration.

Data Quality

Good - comprehensive technical details from DataCamp tutorial, official sites, and GitHub references. Usage requires hands-on setup; no hosted pricing or enterprise data available.

Risk Factors

!
A young model requiring some technical expertise to set-up and utilize properly.
!
Natively, only short clip generation (5-15 seconds).
!
The capability to be deployed is dependent upon the type of consumer-grade hardware used (12 GB + VRAM required).
!
An area where new technologies and potentially other competing models will emerge rapidly.
Last updated: February 2026

What Additional Information Is Available for Wan 2.1?

Technical Architecture

Built on the diffusion transformer (DiT) with Wan-VAE for 1080p encoding/decoding; maintaining temporal consistency and detail. Supports 81 frame generation (5 seconds @ 16 FPS) and offers an adjustable flow shift for motion smoothness.

Model Variants

Offers both a 14B (full capabilities) and a 1.3B (lighter) parameter version; both are open-source and include ComfyUI workflow for local deployment on consumer grade hardware.

Benchmark Leadership

Exceeds performance expectations of open-source and commercial models in 14 areas including: motion quality, style rendering, and multi-target scenarios. This is the first model that generates native English/Chinese text in videos.

Advanced Features

Inspiration mode for artistic expression, sound effects, and quality control negative prompts. Image-to-video with the ability to specify frames so you have total control over your output.

Deployment Accessibility

The application was designed to run on a local GPU that doesn't depend on the cloud. It is free to use and has an open source code base making it perfect for developers who care about their privacy and are using it to create a product or service.

What Are the Best Alternatives to Wan 2.1?

  • •
    Runway ML Gen-3: Commercial text-to-video tool with easy to use web interface and native video support for longer than most other platforms. It is the best choice for developers who want to host a solution and do not want to set up anything technically. (runwayml.com)
  • •
    Luma Dream Machine: The Dream Machine by Lumalabs uses advanced diffusion technology to generate high-quality video with realistic physics and camera controls. Its user interface is much more polished than the others and it can produce much longer clips, however it requires a cloud connection and it is limited as far as how many times you can use it. It is the best solution for professional filmmakers who need to produce cinematic quality video. (lumalabs.ai/dream-machine)
  • •
    Kling AI: China developed video model with excellent motion and lip sync capabilities. Like the previous model, it is focused on both English and Chinese and it offers a hosted service where you pay per token. It would be the best option for companies who are already using tools from the Chinese AI ecosystem. (klingai.com)
  • •
    Stable Video Diffusion: Open Source video model based on Stable Diffusion's image-to-video model. It is easier to set up, however, its motion and text-to-video capabilities are not as good as Wan 2.1. It is the best option for developers who are using HuggingFace and want to quickly animate some images. (huggingface.co/stabilityai/stable-video-diffusion)
  • •
    Pika Labs: Web-based video generator that allows you to generate social media style video clips faster than the others. It also includes lip sync features, however it is limited to lower resolutions and video clip lengths. It is the best option for marketing professionals who are looking to quickly create short-form video content. (pika.art)
  • •
    SVD-XT 1.1: Next Frame Prediction Model, which is an extension of Stable Video Diffusion. It works well for adding more to existing video footage, however, it does not work for generating video from text. It is the best option for developers who want to refine and add to video they generated before. (huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt)

What Is Wan 2.1's Model Overview?

Developer
Alibaba
Version
2.1
Release Date
2025
Architecture
Diffusion Transformers (DiT) + Flow Matching + 3D Causal VAE
Open Source
Yes
Parameters
1.3B, 14B
Status
Generally Available

How Does Wan 2.1's Model Versions Compare?

VersionRelease DateKey Improvements
Wan 2.1 T2V-1.3B2025Efficient text-to-video model
Wan 2.1 T2V-14B2025High-performance text-to-video, leading benchmarks
Wan 2.1 I2V-14B-720P2025Image-to-video at 720p
Wan 2.1 I2V-14B-480P2025Image-to-video at 480p

What Is Wan 2.1's Video Generation Specs?

Max Resolution
1080p (1920x1080)
Max Duration
15 seconds
Frame Rate
16 FPS
Generation Speed
2.5x faster reconstruction than competitors

What Generation Modes Does Wan 2.1 Offer?

Text-to-Video

Create video from text prompts

Image-to-Video

Turn still images into video that looks like it has been animated consistently visually

What Is Wan 2.1's Audio Capabilities Status?

Built-in Audio GenerationNative synced audio and visuals
Lip Sync
Sound Effects
Voice ReferenceNot supported
Music Generation

How Does Wan 2.1's Benchmark Scores Compare?

BenchmarkScoreRankNotes
Internal BenchmarksLeading#1Outperforms open-source and commercial models
External BenchmarksLeading#114B model superior performance
Motion SmoothnessExcellent#1Among open-source models

What Is Wan 2.1's Access Licensing?

Open Source
Yes
License
Open source (details on GitHub presumed)
Self-Hosting
Available
GPU Requirements
Consumer GPU compatible (ComfyUI setup)
Platforms
wan.video, Layer.ai, ComfyUI, AWS ECS

How Does Wan 2.1's Generation Pricing Compare?

TierCostDurationResolutionNotes
Open SourceFreeUp to 15s1080pSelf-hosted
wan.videoFree tierUp to 15s1080pWeb platform
Layer.aiSubscriptionVaries1080pPlatform dependent

What Creative Tools Does Wan 2.1 Offer?

Motion Control

Give smooth motion to cameras and objects

Style Control

Generate realistic and stylized video

Prompt Optimization

Provide detailed control of the elements of your video such as scene, motion, and composition

Negative Prompts

Refine outputs by excluding unwanted elements

What Is Wan 2.1's Content Safety Status?

NSFW FilterChinese model, built-in safeguards likely
Deepfake Prevention
C2PA WatermarkingNot mentioned
Content ModerationPlatform dependent
Usage Logging

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