lllyasviel/FramePack
Lets make video diffusion practical! observed · 2026-10-21
Health v2 · maintenance only
28/100
- Activity 39
- Release rhythm 8
- Longevity 39
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 556
- days_rel: 551
- days_push: 370
- n_releases_24m: 1
Adoption not part of the score
17304 stars · 1739 forks observed · 2026-10-21
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
FramePack is a next-frame-prediction video diffusion framework and desktop application that generates long videos progressively while compressing input contexts to a constant length. It enables 13B-model video generation on consumer GPUs with as little as 6GB of VRAM.
Use cases
- generate long videos from a text prompt locally
- image-to-video generation on a low-VRAM laptop GPU
- run 13B video diffusion models on consumer hardware
- progressive anti-drifting video generation
- create 60-second 30fps videos with a desktop app
When to avoid
- you need an API or hosted web service
- you lack an NVIDIA RTX 30XX/40XX/50XX GPU
- you need macOS support
Facets
application · maturity active
video-processing machine-learning deep-learning llm-inference gui deep-learning artificial-intelligence media windows python video-diffusion text-to-video image-to-video next-frame-prediction generative-ai low-vram video linux gpu desktop
1 source
- readme: https://github.com/lllyasviel/FramePack · fetched 2026-10-21 · 2053ed330a1d
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| lllyasviel/FramePack | main | 28 |
For agents
markdown · JSON · MCP: product_card(name="lllyasviel/FramePack")
Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem