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 France, in May 2025. It comes out of industry.
It works in Language, and is recorded as doing 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
What GPU do I need to run Codestral Embed?
None. Codestral Embed 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 Codestral Embed open source?
No. Codestral Embed has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Codestral Embed have?
No parameter count has been published for Codestral Embed, which is why no memory or speed figure appears on this page.
Who created Codestral Embed?
Codestral Embed was published by Mistral AI, based in France, categorised as industry.
When was Codestral Embed released?
Codestral Embed was published in May 2025.
What is Codestral Embed used for?
Codestral Embed works in Language, and is recorded as handling 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.