Cohere Command
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
- Cohere
- Organisation type
- Industry
- Country
- Canada
- Published
- 1 March 2023
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation
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
- 52B
- Training data
- tokens
52B for larger version https://aws.amazon.com/bedrock/cohere-command-embed/ Cohere Command has had a few different sizes over time and is continuously updated, but there's been a 52B version since at least March 2023: https://twitter.com/percyliang/status/1638236921754443776
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
- Google TPU v4
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
- API access
- Training code
- Unreleased
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Foundation model
- Yes
- Likely above 10²³ FLOP
- Yes
- Record confidence
- Speculative
Sources
Where this record came from and when it was last checked.
- Reference
- World-class AI, at your command
- Last updated
- 28 November 2025
What the numbers mean
Background
Cohere Command was published by Cohere, in the country recorded as Canada, during March 2023. The publishing organisation is categorised as industry.
It works in the domain of Language, and is recorded as performing the task of language modeling/generation.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
Cohere Command — common questions
Cohere Command— 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.
Cohere Command— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Cohere Command— how many parameters does it have?
It has a parameter count of 52B. 52B for larger version https://aws.amazon.com/bedrock/cohere-command-embed/ Cohere Command has had a few different sizes over time and is continuously updated, but there's been a 52B version since at least March 2023: https://twitter.com/percyliang/status/1638236921754443776. 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.
Cohere Command— who created it?
It was published by Cohere, based in Canada, an organisation categorised as industry.
Cohere Command— when was it released?
It was published in March 2023. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
Cohere Command— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling/generation. 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.
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.