T2V-Turbo-v2
No estimate
No hardware requirements for this model
This model's weights are open, but no parameter count has been published for it. Every memory and speed figure starts from that number, so we would rather show nothing than a fabricated estimate.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- University of California Santa Barbara (UCSB),University of California Los Angeles (UCLA),Amazon,University of Waterloo
- Organisation type
- Academia,Academia,Industry,Academia
- Country
- United States of America, Canada
- Published
- 11 October 2024
- Authors
- Jiachen Li, Qian Long, Jian Zheng, Xiaofeng Gao, Robinson Piramuthu, Wenhu Chen, William Yang Wang
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Video
- Task
- Video generation, Text-to-video
- Base model
- VideoCrafter2
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- tokens
8K gradient steps without gradient accumulation.
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA A100
- Chips used
- 8
- Power draw
- 6.3 kW
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Open — downloadable
- Model access
- Open weights (unrestricted)
- Training code
- Open (non-commercial)
apache-2.0 for weights https://huggingface.co/jiachenli-ucsb/T2V-Turbo-v2 no clear license for training code https://github.com/Ji4chenLi/t2v-turbo
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- T2V-Turbo-v2: Enhancing Video Generation Model Post-Training through Data, Reward, and Conditional Guidance Design
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
T2V-Turbo-v2 was published by University of California Santa Barbara (UCSB),University of California Los Angeles (UCLA),Amazon,University of Waterloo, in United States of America, in October 2024. It comes out of academia,Academia,Industry,Academia.
It works in Video, and is recorded as doing video generation, Text-to-video.
It builds on VideoCrafter2, which is why it shares that model's general shape and size.
Published weights mean the model runs on your machine rather than someone else's, which is what makes the hardware question below answerable at all.
Answers
T2V-Turbo-v2 — common questions
What GPU do I need to run T2V-Turbo-v2?
We cannot say. T2V-Turbo-v2 has open weights, but no parameter count has been published for it, and every memory and speed calculation starts from that number. We would rather show nothing than a fabricated estimate.
Is T2V-Turbo-v2 open source?
Its weights are published, so T2V-Turbo-v2 can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.
How many parameters does T2V-Turbo-v2 have?
No parameter count has been published for T2V-Turbo-v2, which is why no memory or speed figure appears on this page.
Who created T2V-Turbo-v2?
T2V-Turbo-v2 was published by University of California Santa Barbara (UCSB),University of California Los Angeles (UCLA),Amazon,University of Waterloo, based in United States of America, categorised as academia,Academia,Industry,Academia.
When was T2V-Turbo-v2 released?
T2V-Turbo-v2 was published in October 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is T2V-Turbo-v2 used for?
T2V-Turbo-v2 works in Video, and is recorded as handling video generation, Text-to-video. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
Where can I download T2V-Turbo-v2?
The weights for T2V-Turbo-v2 are published, though we do not hold a repository link for it. This site calculates hardware requirements rather than hosting model files.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.