FramePack Full Tutorial: 1-Click to Install on Windows - Up to 120 Second Image-to-Videos with 6GB
FramePack from legendary lllyasviel full Windows local tutorial with a very advanced Gradio app to generate consistent videos from images with as long as 120 seconds and as low as 6 GB GPUs. This tutorial will show you step by step how to install and use FramePack locall with a very advanced Graido app. Moreover, I have published installers for cloud services such as RunPod and Massed Compute for those GPU poor and who wants to scale.
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Packing Input Frame Context in Next-Frame Prediction Models for Video Generation
FramePack, to train next-frame (or nextframe-section) prediction models for video generation. The FramePack compresses. Input frames to make the transformer context length a fixed number regardless of the video length.
Paper : https://lllyasviel.github.io/frame_pack_gitpage/pack.pdf
Project Page : https://github.com/lllyasviel/FramePack
Video Chapters
0:00 Intro: New Frame Pack Image-to-Video Framework
0:11 Mind-blowing Features & Why It's Different
0:24 Local Windows Install & Cloud Options (RunPod/Mass Compute)
0:39 Meet the Creator: Legendary LLL YassVL & His Track Record
1:02 Frame Pack Power: Up to 120s, Constant Speed/VRAM, Low VRAM/T-Cache Support
1:30 Live Demo: Generating 3 Videos at Once
1:52 CRITICAL Pre-Install Step: Windows Requirements Check
2:03 Preparing for Install: Moving File & Disk Space (50GB+)
2:14 How to Install: Extracting & Running the .bat File
2:28 Automatic Installation Process Overview
2:45 Technical Detail: Hunyuan Backend (Future 1.2.1 Support?)
2:57 Frame Pack Explained: Prediction Network & High Frame Counts
3:20 Live Generation Preview Feature (Second-by-Second Output)
3:37 Cloud vs. Local Performance: Delays & Comparisons
4:00 Installation Complete! How to Verify
4:16 Automatic Model Downloading on First Launch
4:27 Where Models Are Saved (models folder)
4:44 Troubleshooting Download Failures: Editing startup.bat Fix (Set to 0)
5:08 Download Fix Options: Restarting vs. Editing .bat File
5:27 Launching Pre-Installed Version & Checking Models Folder
5:39 Starting Application: Model Loading Process (CPU - VRAM)
5:53 Using Google Studio AI (Gemini Pro) to Generate Prompts
6:14 Crafting a "Hunyuan Image-to-Video Prompt"
6:34 Exploring Generation Options: T-Cache, Seed, Length, Steps
6:56 Options: Distill CFG, GPU Memory Preservation
7:11 Tool Tip: How to Install & Use nvitop for VRAM Monitoring
7:30 NEW FEATURE: Improved Video Quality Control (Encoding Fix)
7:41 Quality Settings: High, Medium, Low, Web Compatible
8:09 Starting Live Demo (10s) - Note: Version 1, More Features Coming!
8:26 Watching Live Generation: GPU Wattage Monitoring & Efficiency
8:51 Wattage Explained: Shared vs. Dedicated VRAM Power Draw
9:10 Live Preview: First Second Rendered & Displayed
9:23 Generating Subsequent Seconds & Benefit of Live Preview
9:36 Understanding T-Cache Speed (Slow Start, Fast Finish)
9:59 Live Preview: Second Second Rendered (Video Updated)
10:14 Watching Full Generation Progress & VRAM Check
10:35 Reviewing Completed Generations from Cloud Instances
10:55 Analysis Result 2: Another High Accuracy Example
11:03 Result 3 Failed - Likely Needs a Better Prompt
11:26 Understanding Output Video Resolution (Variable)
11:37 Future Plans: Resolution Control & Recap (Rush Release)
11:54 Cloud Setup: Overview & Mass Compute Details (Coupon)
12:21 Mass Compute GPUs: RTX A6000 Ada Rec, H100/A100 Pricing
12:48 RunPod Setup Details: Instructions & Required Template
13:06 Final Thoughts & Future Plans (Batch Processing, Presets)
13:25 Aiming for Feature Parity with 1.2.1 Application
13:39 Teaser: New Improved Super Upscaling App Coming Soon
14:01 Links & Thank You
Song: Cartoon, Jéja - Why We Lose (feat. Coleman Trapp) [NCS Release]
Music provided by NoCopyrightSounds
Free Download/Stream: http://ncs.io/whywelose
Watch: http://youtu.be/zyXmsVwZqX4
And few others : https://gist.github.com/FurkanGozukara/8fa15b67370a53af6394da239d2fce8e
Comments (14)
I just want to let you know that most of the installer use this pip install --pre torch==2.7.0.dev20250311 torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128 Which do no more exist since it is stable so need to update those installer
it doesnt use it anymore. download v61 zip file and make a fresh folder install
The model refuse to download for me I have tried all your recommendations still don't work. It is like it freezes
let me upgrade model downloader for you give me some time
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 108.00 MiB. GPU 0 has a total capacity of 12.00 GiB of which 6.12 GiB is free. Of the allocated memory 4.80 GiB is allocated by PyTorch, and 34.66 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
restart pc and make sure your entire VRAM is free. also set virtual ram to 50 GB
When it generates a new 1 second section of a video, is it taking the whole previous second into account or doing an image to video on the last frame from the previously generated 1 second video? Ideally it would take the previous 1 second video into account (or at least multiple frames of it rather than one frame), but when I generate an image 2 video of a scene that has a crowd of people in it, one person walks one way for one second then instantly switches to walking in the opposite direction for the next second which makes it seem like it's only taking 1 frame into account to continue from and so not being consistent for that part. Is that setting controllable? Also (like was maybe suggested in the video or somewhere else), it would be good if we can specify the resolution of the video we want to create (width, height and maybe aspect ratio selection) and maybe frame rate. Also if you set the video length to exactly 5 seconds in the UI, for me, the video it creates is 4 secs 834 millisecs (according to mediainfo), 30.0 fps, so not quite 5 seconds. So it seems that's a slight error. If there's a way to create Loras with it that would be good too. Also it could help if the output folder also could output a .txt file with the prompt that was used to create the video and the settings used.
it takes whole second of previous second. it could be even all seconds i am not sure but it is not last frame extension totally different i will look for lora thing
I installed it, nicely done btw. when I do a picture to video it uses 24Gb Gpu, is not bad, but is not 6Gb, I tested 2 on the 3090 Suprime and RTX 5090. Is it possible to set somewhere how much gpu you use? it is very fast I must say. Greetings William
as i said it uses all available vram dynamically
For new features, if it's generating it out of sequence (last bit first) and generating it in steps, a second at a time, and it's using the whole prompt for each section it generates, couldn't there be an option where you specified a different prompt for specific timecodes in the video, so you could make different things happen starting from different timecodes? eg. 0: the man picks up the sword, 10: the man walks away, etc.
i dont know if possible atm.
Any idea on how to make it available on 0.0.0.0 rather than localhost?
i really dont want to edit app file to provide it as args as it causes so many issues but if you need you can edit app file and add yourself block.launch( share=args.share, inbrowser=True, server_name=0.0.0.0, server_port=7860, )