Theseus
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
- Bell Laboratories
- Organisation type
- Industry
- Country
- United States of America
- Published
- 2 July 1950
- Authors
- Claude Shannon
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Robotics
- Task
- Maze solving
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
- 0K
- Training data
- 40 tokens
The learned part is the maze configuration. There are 25 squares of the maze. The 16 squares to the left top corner have each one adjacent square down and one adjacent square up, for a total of 16*2 walls. We only need to count the 8 spare walls connecting the squares in the right side and the bottom side. In total there are 16*2+8 walls.
Each wall Theseus bumps into is a datapoint
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.
- Training compute
- 4 × 10¹ FLOP
- How it was established
- Other
The "training" consists on the mouse running around and checking each wall (assuming each relay switch is one operation).
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Frontier model
- Yes
- Why it is tracked
- Historical significance
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- Mighty Mouse
- Last updated
- 28 November 2025
What the numbers mean
Background
Theseus was published by Bell Laboratories, in the country recorded as United States of America, during July 1950. The category the publisher falls under is industry.
It works in the domain of Robotics, and is recorded as performing the task of maze solving.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
What went into building it
Producing it required arithmetic totalling around 4 × 10¹ FLOP. That figure measures what producing the model cost, and has no bearing on how fast it answers.
Training consumed a corpus of around 40 tokens of text.
It is tracked in the underlying dataset for one reason in particular: historical significance.
Answers
Theseus — common questions
Theseus— 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.
Theseus— how many parameters does it have?
It has a parameter count of 0K. The learned part is the maze configuration. There are 25 squares of the maze. The 16 squares to the left top corner have each one adjacent square down and one adjacent square up, for a total of 16*2 walls. We only need to count the 8 spare walls connecting the squares in the right side and the bottom side. In total there are 16*2+8 walls. 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.
Theseus— who created it?
It was published by Bell Laboratories, based in United States of America, an organisation categorised as industry.
Theseus— when was it released?
It was published in July 1950. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Theseus— what is it used for?
It works in the domain of Robotics, and is recorded as handling the task of maze solving. These are the areas it was designed around; they describe intent rather than a hard boundary.
Theseus— how much compute was used to train it?
Training consumed around 4 × 10¹ FLOP. That measures what producing the model cost and says nothing about how quickly it answers once trained — inference speed comes from memory bandwidth, not from the training budget.
Theseus— 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.
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.