Model profile

AnimateDiff AI video generator

A foundational community project for adding motion modules to image diffusion models.

Should You Use AnimateDiff?

Use it for: motion modules, community workflows, stylized animation

Skip or compare first if: Not a modern standalone foundation video model. Output quality depends heavily on the underlying image model and workflow.

Positioning: A foundational community project for adding motion modules to image diffusion models.

Top Capabilities

  • Motion modules for diffusionAnimateDiff introduced reusable motion modules for personalized text-to-image diffusion models.Source
  • Primary source-backed profileAnimateDiff has an official source, repository, paper, or model card attached for verification.Source
  • Open/self-hosted access pathAnimateDiff can be evaluated through open code, weights, or model-card resources when license terms allow.Source

Company Snapshot

Company profile is not yet attached to this model.

Price, Access, Open Status

Access: Open Weights, Research Only

Open/closed: Open. Open code, weights, or model-card resources are listed; verify license terms before commercial use.

Open/self-hosted; cost depends on local or cloud GPU.

Price, regional access, and commercial terms need a live check before cost-sensitive recommendations.

Latest Version

AnimateDiff

2023-07 / confirmed

Open motion-module approach for animating image diffusion models.

Latest News

AnimateDiff GitHub repository

2026 / guoyww GitHub

External source link for this model.

Open original

Why It Ranks Here

Rank: #38 52

Score source: Provisional quality proxy based on official/research evidence and catalogue presence; exact external rank requires live leaderboard/API collection.. Evidence confidence is medium.

Rankings Methodology

Key Score Drivers

These are the scoring dimensions most responsible for the current ranking position.

  • Model Quality Proxy: 55Provisional quality proxy based on official/research evidence and catalogue presence; exact external rank requires live leaderboard/API collection.
  • Ecosystem Popularity: 100GitHub snapshot includes 1 repo(s), 12,201 stars, 1,088 forks, 319 open issues, latest pushed 2024-07-31T01:14:15Z.
  • Capability Depth: 45Supported workflow tags: image_animation, motion_module, open_weights. Depth rewards T2V/I2V/V2V, references, native audio, editing, API, and open weights where present.
  • Version Maturity: 582 version/history entries in the profile; latest public date is 2023-2024.

Alternatives And Comparisons

Use these when price, access, output style, or workflow fit is uncertain.

  • SeedanceByteDance's frontier video generation family for multimodal, audio-video, short-form, and cinematic creator workflows.View modelCompare
  • KlingKuaishou's broad AI video and image generation platform for text-to-video, image-to-video, native audio, references, and creator effects.View modelCompare
  • PixVerseA creator-friendly AI video platform with strong API coverage for text-to-video, image-to-video, transitions, extension, and reference fusion.View modelCompare
  • ViduShengShu Technology's video model family for native audio-video storytelling, image-to-video, and scene-oriented short-form production.View modelCompare

What It Is

Primary content is rendered into static HTML.

AnimateDiff is a classic open project for animating image diffusion models with motion modules. It is not a current all-in-one frontier video model, but it has had major influence on the community ecosystem, ComfyUI workflows, and stylized animation.

Include it as a historical/open baseline and as an adjacent technology for motion transfer and image animation.

Version Progress

  • 2023-07 / confirmed / confirmedAnimateDiffOpen motion-module approach for animating image diffusion models.

Open / Source Evidence

Status: Open

Open code, weights, or model-card resources are listed; verify license terms before commercial use.

Latest News

Model-specific news entries link directly to the original publisher; article bodies stay off-site.

Full Score Breakdown

Weighted evidence dimensions separate model quality from access, web authority, ecosystem, and source confidence. See methodology and rankings.

DimensionScoreWeightEvidenceConfidence
Model Quality Proxy 55 24% Provisional quality proxy based on official/research evidence and catalogue presence; exact external rank requires live leaderboard/API collection. medium
Missing: live Artificial Analysis rank/Elo by modality, live Arena AI rank/score by modality
Capability Depth 45 16% Supported workflow tags: image_animation, motion_module, open_weights. Depth rewards T2V/I2V/V2V, references, native audio, editing, API, and open weights where present. medium
Missing: hands-on feature verification, mode-specific limits by duration/resolution
Access And Pricing 30 12% Access types: open_weights, research_only. Pricing note: Open/self-hosted; cost depends on local or cloud GPU. low
Missing: current free tier, normalized price per video minute
Version Maturity 58 12% 2 version/history entries in the profile; latest public date is 2023-2024. medium
Missing: automated release-note monitor, model ID/version mapping across providers
Ecosystem Popularity 100 10% GitHub snapshot includes 1 repo(s), 12,201 stars, 1,088 forks, 319 open issues, latest pushed 2024-07-31T01:14:15Z. high
Missing: Hugging Face downloads/likes, Replicate/fal usage/runs
Web Authority 28 10% SEO snapshot found product domain github.com and company domain unknown; sampled sitemap URL count is unknown.

No public source link is attached yet.

medium
Missing: Similarweb/API traffic, Tranco rank
Company Distribution 30 10% Company profile is missing; distribution score is provisional. low
Missing: app store ratings/review volume, product MAU/traffic
Source Confidence 94 6% Profile source confidence is confirmed with 2 official URL(s), 1 feature evidence item(s), SEO present, GitHub present. high
Missing: paid/API evidence refresh, manual output review artifacts

Limitations And Pricing

Open/self-hosted; cost depends on local or cloud GPU.

  • Not A Modern Standalone Foundation Video Model.
  • Output Quality Depends Heavily On The Underlying Image Model And Workflow.