A.X (Adot) 18B
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
- SK Telecom
- Organisation type
- Industry
- Country
- Korea (Republic of)
- Published
- 15 November 2021
- Authors
- Deuksin Kwon, Sunwoo Lee, Ki Hyun Kim, Seojin Lee, Taeyoon Kim, Eric Davis
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language, Speech
- Task
- Chat
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
- 18B
- 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
- 1.4 × 10¹⁸ FLOP
- How it was established
- Operation counting
=18000000000 parameters *12500000 training tokens * 6 FLOP/token/parameter=1350000000000000000=1.35 × 10^18 FLOP unsure about training dataset size->speculative confidence level
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
- NVIDIA A100 SXM4 80 GB
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.
- 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
- Speculative
Sources
Where this record came from and when it was last checked.
- Reference
- WHAT, WHEN, and HOW to Ground: Designing User Persona-Aware Conversational Agents for Engaging Dialogue
- Last updated
- 11 February 2026
What the numbers mean
Background
A.X (Adot) 18B was published by SK Telecom, in the country recorded as Korea (Republic of), during November 2021. The publishing organisation is categorised as industry.
It works in the domain of Language, Speech, and is recorded as performing the task of chat.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
How it was trained
Training it took a computation budget of roughly 1.4 × 10¹⁸ FLOP, on hardware recorded as NVIDIA A100 SXM4 80 GB. That figure measures what producing the model cost, and has no bearing on how fast it answers.
Answers
A.X (Adot) 18B — common questions
A.X (Adot) 18B— how much compute was used to train it?
Training consumed around 1.4 × 10¹⁸ FLOP, on hardware recorded as NVIDIA A100 SXM4 80 GB. 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.
A.X (Adot) 18B— 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.
A.X (Adot) 18B— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
A.X (Adot) 18B— how many parameters does it have?
It has a parameter count of 18B. 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.
A.X (Adot) 18B— who created it?
It was published by SK Telecom, based in Korea (Republic of), an organisation categorised as industry.
A.X (Adot) 18B— when was it released?
It was published in November 2021. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
A.X (Adot) 18B— what is it used for?
It works in the domain of Language, Speech, and is recorded as handling the task of chat. 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.