Codestral Embed
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
- Mistral AI
- Organisation type
- Industry
- Country
- France
- Published
- 28 May 2025
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Code generation, Code autocompletion, Retrieval-augmented 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.
- Training data
- tokens
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
Codestral Embed is available on our API under the name `codestral-embed-2505` at a price of $0.15 per million tokens. It is also available on our batch API at a 50% discount. For on-prem deployments, please contact us to connect with our applied AI team.
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Likely above 10²³ FLOP
- Yes
- Record confidence
- Unknown
Sources
Where this record came from and when it was last checked.
- Reference
- The new state-of-the-art embedding model for code.
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Codestral Embed was published by Mistral AI, in the country recorded as France, during May 2025. It comes out of an organisation categorised as industry.
It works in the domain of Language, and is recorded as performing the task of code generation, Code autocompletion, Retrieval-augmented generation.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
Codestral Embed — common questions
Codestral Embed— 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.
Codestral Embed— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Codestral Embed— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
Codestral Embed— who created it?
It was published by Mistral AI, based in France, an organisation categorised as industry.
Codestral Embed— when was it released?
It was published in May 2025.
Codestral Embed— what is it used for?
It works in the domain of Language, and is recorded as handling the task of code generation, Code autocompletion, Retrieval-augmented generation. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
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.