RAAM
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.
- Published
- 1 November 1990
- Authors
- Jordan B. Pollack
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Other
- Task
- Representation learning
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
- 1.5K
- Training data
- 29 tokens
Largest model: "A 48-16-48 RAAM learned to construct representations " Parameters 48*16*2 = 1536
29 sentence fragments (Figure 10)
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Highly cited
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- Recursive Distributed Representations
- Last updated
- 28 November 2025
What the numbers mean
Background
RAAM was published by its authors, in November 1990.
It works in Other, and is recorded as doing representation learning.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
It was trained on about 29 tokens of text.
It is tracked in the underlying dataset for one reason in particular: highly cited.
Answers
RAAM — common questions
What GPU do I need to run RAAM?
None. RAAM 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 RAAM open source?
The licensing for RAAM was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does RAAM have?
RAAM has 1.5K parameters. Largest model: "A 48-16-48 RAAM learned to construct representations " Parameters 48*16*2 = 1536. 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.
When was RAAM released?
RAAM was published in November 1990. 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 RAAM used for?
RAAM works in Other, and is recorded as handling representation learning. These are the areas it was designed around; they describe intent rather than a hard boundary.
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.