Eagle 2.5
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,Nanjing University,Hong Kong Polytechnic University,Rutgers University
- Organisation type
- Industry,Academia,Academia,Academia
- Country
- United States of America, China, Hong Kong
- Published
- 21 April 2025
- Authors
- Guo Chen, Zhiqi Li, Shihao Wang, Jindong Jiang, Yicheng Liu, Lidong Lu, De-An Huang, Wonmin Byeon, Matthieu Le, Tuomas Rintamaki, Tyler Poon, Max Ehrlich, Tuomas Rintamaki, Tyler Poon, Tong Lu, Limin Wang, Bryan Catanzaro, Jan Kautz, Andrew Tao, Zhiding Yu, Guilin Liu
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision, Robotics, Language
- Base model
- Qwen2.5-7B
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
- 8B
- Training data
- tokens
Table 8. "Full Model, 8B" Could be Qwen2.5-7B + MLP Connector (40M) https://nvlabs.github.io/EAGLE/ as of 2025-05-29: "Eagle-2.5 Weights (Coming Soon)"
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- Eagle 2.5: Boosting Long-Context Post-Training for Frontier Vision-Language Models
- Last updated
- 28 November 2025
What the numbers mean
Background
Eagle 2.5 was published by NVIDIA,Nanjing University,Hong Kong Polytechnic University,Rutgers University, in the country recorded as United States of America, during April 2025. The publishing organisation is categorised as industry,Academia,Academia,Academia.
It works in the domain of Vision, Robotics, Language.
Its starting point was an existing base model, Qwen2.5-7B. That is why it shares the base model's general shape and size.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Answers
Eagle 2.5 — common questions
Eagle 2.5— when was it released?
It was published in April 2025.
Eagle 2.5— what is it used for?
It works in the domain of Vision, Robotics, Language. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
Eagle 2.5— what GPU do I need to run it?
None. This 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.
Eagle 2.5— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
Eagle 2.5— how many parameters does it have?
It has a parameter count of 8B. Table 8. "Full Model, 8B" Could be Qwen2.5-7B + MLP Connector (40M) https://nvlabs.github.io/EAGLE/ as of 2025-05-29: "Eagle-2.5 Weights (Coming Soon)". 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.
Eagle 2.5— who created it?
It was published by NVIDIA,Nanjing University,Hong Kong Polytechnic University,Rutgers University, based in United States of America, an organisation categorised as industry,Academia,Academia,Academia.
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.