VARCO LLM KO/EN-13B-IST ver.1
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
- NCSOFT
- Organisation type
- Industry
- Country
- Korea (Republic of)
- Published
- 16 August 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
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
- 13B
- Training data
- 350,000,000,000 tokens
https://ncsoft.github.io/ncresearch/varco-llm-details/
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
- 2.7 × 10²² FLOP
- How it was established
- Operation counting
=350000000000*6*13000000000=2.73 × 10^22
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
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
Sources
Where this record came from and when it was last checked.
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
VARCO LLM KO/EN-13B-IST ver.1 was published by NCSOFT, in Korea (Republic of), in August 2023. industry is the category the publisher falls under.
It works in Language, and is recorded as doing language modeling/generation, Chat.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
What went into building it
Training it took roughly 2.7 × 10²² FLOP of computation — a measure of what producing the model cost, not of how fast it answers.
It was trained on about 350,000,000,000 tokens of text.
Answers
VARCO LLM KO/EN-13B-IST ver.1 — common questions
How many parameters does VARCO LLM KO/EN-13B-IST ver.1 have?
VARCO LLM KO/EN-13B-IST ver.1 has 13B parameters. 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.
Who created VARCO LLM KO/EN-13B-IST ver.1?
VARCO LLM KO/EN-13B-IST ver.1 was published by NCSOFT, based in Korea (Republic of), categorised as industry.
When was VARCO LLM KO/EN-13B-IST ver.1 released?
VARCO LLM KO/EN-13B-IST ver.1 was published in August 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.
What is VARCO LLM KO/EN-13B-IST ver.1 used for?
VARCO LLM KO/EN-13B-IST ver.1 works in Language, and is recorded as handling language modeling/generation, Chat. These are the areas it was designed around; they describe intent rather than a hard boundary.
How much compute was used to train VARCO LLM KO/EN-13B-IST ver.1?
Around 2.7 × 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.
What GPU do I need to run VARCO LLM KO/EN-13B-IST ver.1?
None. VARCO LLM KO/EN-13B-IST ver.1 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 VARCO LLM KO/EN-13B-IST ver.1 open source?
No. VARCO LLM KO/EN-13B-IST ver.1 has not had its weights published, so it exists only as a service controlled by its owner.
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.