EXAONE 3.5-R 2.4B

Closed weights LG AI Research 2.4B parameters March 2025

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
LG AI Research
Organisation type
Industry
Country
Korea (Republic of)
Published
14 March 2025

What it does

The problem areas the model was built for. A model can carry several of each.

Domain
Language
Task
Language modeling/generation, Question answering, Translation
Base model
EXAONE 3.5 2.4B

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
2.4B

2.4B

Training data
tokens

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
9.5 × 10²² FLOP

9.36 × 10^22 (base model reported training compute) + 1.44 × 10^21 (finetune compute) = 9.504e+22 FLOP

How it was established
Reported
Fine-tuning compute
1.4 × 10²¹ FLOP

1.44e21

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
Unreleased
Training code
Unreleased

How it is classified

Labels the source dataset applies when tracking notable models, and how confident it is in the entry.

Record confidence
Confident

Sources

Where this record came from and when it was last checked.

Last updated
28 November 2025

What the numbers mean

Background

EXAONE 3.5-R 2.4B was published by LG AI Research, in the country recorded as Korea (Republic of), during March 2025. The category the publisher falls under is industry.

It works in the domain of Language, and is recorded as performing the task of language modeling/generation, Question answering, Translation.

It builds on EXAONE 3.5 2.4B. Most models at this scale are adapted from an existing base rather than built from nothing.

Its weights were never published, so it can only be reached through its provider. No graphics card changes that.

What went into building it

Producing it required arithmetic totalling around 9.5 × 10²² FLOP. That figure measures what producing the model cost, and has no bearing on how fast it answers.

Answers

EXAONE 3.5-R 2.4B — common questions

01

EXAONE 3.5-R 2.4B— when was it released?

It was published in March 2025.

02

EXAONE 3.5-R 2.4B— what is it used for?

It works in the domain of Language, and is recorded as handling the task of language modeling/generation, Question answering, Translation. 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.

03

EXAONE 3.5-R 2.4B— how much compute was used to train it?

Training consumed around 9.5 × 10²² 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.

04

EXAONE 3.5-R 2.4B— 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.

05

EXAONE 3.5-R 2.4B— is it open source?

No. Its weights have not been published, so it exists only as a service controlled by its owner.

06

EXAONE 3.5-R 2.4B— how many parameters does it have?

It has a parameter count of 2.4B. 2.4B. 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.

07

EXAONE 3.5-R 2.4B— who created it?

It was published by LG AI Research, based in Korea (Republic of), an organisation categorised as industry.

Source

Record last updated 28 November 2025

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