VILA-7B
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
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
- NVIDIA,Massachusetts Institute of Technology (MIT)
- Organisation type
- Industry,Academia
- Country
- United States of America
- Published
- 15 May 2024
- Authors
- Ji Lin, Hongxu Yin, Wei Ping, Yao Lu, Pavlo Molchanov, Andrew Tao, Huizi Mao, Jan Kautz, Mohammad Shoeybi, Song Han
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Multimodal, Language, Vision, Video
- Task
- Chat, Visual question answering, Image captioning, Language modeling/generation, Question answering
- Base model
- Llama 2-7B
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.
- Parameters
- 7B
- Training data
- tokens
Training compute
The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.
- How it was established
- Hardware
- Fine-tuning compute
- 1.7 × 10²¹ FLOP
312000000000000 FLOP/GPU/sec * 5100 GPU-hours * 3600 sec / hour * 0.3 [assumed utilization] = 1.718496e+21 FLOP
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
- 128
- Chip-hours
- 5,100
- Power draw
- 101.1 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
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Unreleased
- Hugging Face
- Efficient-Large-Model
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
- Citations
- 827
Sources
Where this record came from and when it was last checked.
- Reference
- VILA: On Pre-training for Visual Language Models
- Last updated
- 25 May 2026
What the numbers mean
What this model is
VILA-7B was published by NVIDIA,Massachusetts Institute of Technology (MIT), in United States of America, in May 2024. It comes out of industry,Academia.
It works in Multimodal, Language, Vision, Video, and is recorded as doing chat, Visual question answering, Image captioning, Language modeling/generation, Question answering.
It is derived from Llama 2-7B rather than trained from scratch, which is the usual way a specialised model is produced.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
VILA-7B — common questions
What is VILA-7B used for?
VILA-7B works in Multimodal, Language, Vision, Video, and is recorded as handling chat, Visual question answering, Image captioning, Language modeling/generation, Question answering. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run VILA-7B?
None. VILA-7B is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is VILA-7B open source?
No. VILA-7B has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does VILA-7B have?
VILA-7B has 7B parameters. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Who created VILA-7B?
VILA-7B was published by NVIDIA,Massachusetts Institute of Technology (MIT), based in United States of America, categorised as industry,Academia.
When was VILA-7B released?
VILA-7B was published in May 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.
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.