Konan LLM 41B
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
- Konan Technology
- Organisation type
- Industry
- Country
- Korea (Republic of)
- Published
- 15 December 2023
- Authors
- Yang Seung-hyun, Wiretin, Changmin, Kim Jong-tae
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language, Vision
- Task
- Language modeling/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.
- Parameters
- 41B
- Training data
- 7,000,000,000,000 tokens
https://www.konantech.com/pr/press?number=2628&pn=1&stype2=&sfi=subj&sword= Since 2007, via the real-time AI analysis service pulseK, over 20.5 billion pieces of data have been independently secured. Among them, only 2 billion high-quality, large-scale data pieces have been used for training.
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
- 1.7 × 10²³ FLOP
- How it was established
- Operation counting
=41000000000 parameters * 700000000000 tokens [see dataset size notes] * 6 FLOP / token / parameter =1.722 × 10^23 FLOP
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
- Likely
Sources
Where this record came from and when it was last checked.
- Reference
- Konan LLM: A Korean Large Language Model
- Last updated
- 28 November 2025
What the numbers mean
About this model
Konan LLM 41B was published by Konan Technology, in the country recorded as Korea (Republic of), during December 2023. The category the publisher falls under is industry.
It works in the domain of Language, Vision, and is recorded as performing the task of language modeling/generation.
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
Producing it required arithmetic totalling around 1.7 × 10²³ FLOP. That figure measures what producing the model cost, and has no bearing on how fast it answers.
Training consumed a corpus of around 7,000,000,000,000 tokens of text.
Answers
Konan LLM 41B — common questions
Konan LLM 41B— who created it?
It was published by Konan Technology, based in Korea (Republic of), an organisation categorised as industry.
Konan LLM 41B— when was it released?
It was published in December 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.
Konan LLM 41B— what is it used for?
It works in the domain of Language, Vision, and is recorded as handling the task of language modeling/generation. These are the areas it was designed around; they describe intent rather than a hard boundary.
Konan LLM 41B— how much compute was used to train it?
Training consumed around 1.7 × 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.
Konan LLM 41B— 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.
Konan LLM 41B— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Konan LLM 41B— how many parameters does it have?
It has a parameter count of 41B. 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.
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.