FramePack AI 视频生成器
An open long-video/image-to-video technique that compresses frame context to extend generation length.
是否适合使用 FramePack?
适合用来做： long-video experiments, image-to-video research, open workflow testing
Skip or compare first 的情况: Better treated as a method/workflow than a standalone commercial model. Needs active maintenance review.
定位： An open long-video/image-to-video technique that compresses frame context to extend generation length.
核心能力
- Frame-context packingFramePack targets longer video generation by packing frame context efficiently.来源
- Primary source-backed profileFramePack has an official source, repository, paper, or model card attached for verification.来源
- Open/self-hosted access pathFramePack can be evaluated through open code, weights, or model-card resources when license terms allow.来源
公司摘要
公司 profile is not yet attached to this model.
价格、入口与开源状态
访问方式： Open 权重s, Research Only
开源/闭源： 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.
最新版本
FramePack
2025 / partial
Community release focused on longer video generation workflows.
关键得分驱动
These are the scoring dimensions most responsible for the current ranking position.
- 模型 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.
- 来源 Confidence: 74Profile source confidence is partial with 1 official URL(s), 1 feature evidence item(s), SEO present, GitHub present.
替代选择与对比
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 model对比
- KlingKuaishou's broad AI video and image generation platform for text-to-video, image-to-video, native audio, references, and creator effects.View model对比
- PixVerseA creator-friendly AI video platform with strong API coverage for text-to-video, image-to-video, transitions, extension, and reference fusion.View model对比
- ViduShengShu Technology's video model family for native audio-video storytelling, image-to-video, and scene-oriented short-form production.View model对比
它是什么
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 / the most important evaluation dimensions for future AI video tools.
版本进展
- FramePackCommunity release focused on longer video generation workflows.
开源 / 来源证据
Status: Open
Open code, weights, or model-card resources are listed; verify license terms before commercial use.
最新消息
模型-specific news entries link directly to the original publisher; article bodies stay off-site.
- FramePack GitHub repository External source link for this model. 打开原文
完整得分拆解
权重ed evidence dimensions separate model quality from access, web authority, ecosystem, and source confidence. See methodology and rankings.
| 维度 | Score | 权重 | 证据 | Confidence |
|---|---|---|---|---|
| 模型 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 |
| 公司 Distribution | 30 | 10% | 公司 profile is missing; distribution score is provisional. | low |
| 来源 Confidence | 74 | 6% | Profile source confidence is partial with 1 official URL(s), 1 feature evidence item(s), SEO present, GitHub present. | medium |
限制与价格
Open/self-hosted; cost depends on hardware and integrated model.