FramePack AI video generator
An open long-video/image-to-video technique that compresses frame context to extend generation length.
Should You Use FramePack?
Use it for: long-video experiments, image-to-video research, open workflow testing
Skip or compare first if: Better treated as a method/workflow than a standalone commercial model. Needs active maintenance review.
Positioning: An open long-video/image-to-video technique that compresses frame context to extend generation length.
Top Capabilities
- Frame-context packingFramePack targets longer video generation by packing frame context efficiently.Source
- Primary source-backed profileFramePack has an official source, repository, paper, or model card attached for verification.Source
- Open/self-hosted access pathFramePack 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/self-hosted; cost depends on hardware and integrated model.
Price, regional access, and commercial terms need a live check before cost-sensitive recommendations.
Latest Version
FramePack
2025 / partial
Community release focused on longer video generation workflows.
Why It Ranks Here
Rank: #40 51
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.
Key Score Drivers
These are the scoring dimensions most responsible for the current ranking position.
- Model Quality Proxy: 60Provisional 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), 17,161 stars, 1,731 forks, 486 open issues, latest pushed 2025-10-16T01:28:50Z.
- Capability Depth: 56Supported workflow tags: i2v, long_video, open_weights. Depth rewards T2V/I2V/V2V, references, native audio, editing, API, and open weights where present.
- Source Confidence: 74Profile source confidence is partial with 1 official URL(s), 1 feature evidence item(s), SEO present, GitHub present.
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.
FramePack is an open community project from lllyasviel focused on longer video generation using frame-context packing. It is a method and workflow direction more than a polished consumer model.
For the benchmark site, include FramePack under open/research because long-video continuity is one of the most important evaluation dimensions for future AI video tools.
Version Progress
- FramePackCommunity release focused on longer video generation workflows.
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.
- FramePack GitHub repository External source link for this model. Open original
Full Score Breakdown
Weighted evidence dimensions separate model quality from access, web authority, ecosystem, and source confidence. See methodology and rankings.
| Dimension | Score | Weight | Evidence | Confidence |
|---|---|---|---|---|
| Model Quality Proxy | 60 | 24% | Provisional quality proxy based on official/research evidence and catalogue presence; exact external rank requires live leaderboard/API collection. | low |
| Capability Depth | 56 | 16% | Supported workflow tags: i2v, long_video, open_weights. Depth rewards T2V/I2V/V2V, references, native audio, editing, API, and open weights where present. | medium |
| Access And Pricing | 30 | 12% | Access types: open_weights, research_only. Pricing note: Open/self-hosted; cost depends on hardware and integrated model. | low |
| Version Maturity | 28 | 12% | 1 version/history entries in the profile; latest public date is 2025. | medium |
| Ecosystem Popularity | 100 | 10% | GitHub snapshot includes 1 repo(s), 17,161 stars, 1,731 forks, 486 open issues, latest pushed 2025-10-16T01:28:50Z. | high |
| 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 |
| Company Distribution | 30 | 10% | Company profile is missing; distribution score is provisional. | low |
| Source Confidence | 74 | 6% | Profile source confidence is partial with 1 official URL(s), 1 feature evidence item(s), SEO present, GitHub present. | medium |
Limitations And Pricing
Open/self-hosted; cost depends on hardware and integrated model.