LightOn Mini
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
- LightOn
- Organisation type
- Industry
- Country
- France
- Published
- 21 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, Chat
- Approach
- Self-supervised 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
- 40B
- Training data
- 1,000,000,000,000 tokens
"Boasting an impressive 40 billion parameters, Mini is a formidable addition to the growing array of language models available in the market today."
"The amount of data in Mini corpus is 1 trillion tokens. We mainly used data from the public web to pre-train our model, with strong filtering, toxicity reduction, and deduplication to ensure that only high-quality data is retained." assuming 0.75 words per token - 750000000000.0 words
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
- 2.4 × 10²³ FLOP
- How it was established
- Operation counting
6ND aproximation: 6*40B*1T = 2.4e23
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
- Hosted access (no API)
- Training code
- Unreleased
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
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- LightOn's Large Language Model of 40 billion parameters: MINI
- Last updated
- 28 November 2025
What the numbers mean
What this model is
LightOn Mini was published by LightOn, in the country recorded as France, during March 2023. It comes out of an organisation categorised as industry.
It works in the domain of Language, and is recorded as performing the task of language modeling/generation, Chat.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
How it was trained
Training it took a computation budget of roughly 2.4 × 10²³ FLOP. That figure measures what producing the model cost, and has no bearing on how fast it answers.
It was trained on a corpus of about 1,000,000,000,000 tokens of text.
Answers
LightOn Mini — common questions
LightOn Mini— how much compute was used to train it?
Training consumed around 2.4 × 10²³ 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.
LightOn Mini— 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.
LightOn Mini— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
LightOn Mini— how many parameters does it have?
It has a parameter count of 40B. "Boasting an impressive 40 billion parameters, Mini is a formidable addition to the growing array of language models available in the market today.". 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.
LightOn Mini— who created it?
It was published by LightOn, based in France, an organisation categorised as industry.
LightOn Mini— 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.
LightOn Mini— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling/generation, Chat. 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.