Solar Open 100B
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
- Upstage
- Organisation type
- Industry
- Country
- Korea (Republic of)
- Published
- 31 December 2025
- Authors
- Upstage AI
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
- 102B
- Training data
- 19,700,000,000,000 tokens
102B, of which 12B active
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 × 10²⁴ FLOP
In direct correspondence with Epoch AI, Upstage confirmed that the training cost of Solar Open 100B was ~$8.4 million. using 6 * active parameters * training tokens, training FLOP is 6 * 12 billion * 19 trillion = ~1.4e24 FLOP
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Wall-clock time
- 1,572 hours (65.5 days)
"Approx. 65.5 days (Net training time excluding downtime)" per email
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.
- Why it is tracked
- Training cost
- Record confidence
- Confident
Sources
Where this record came from and when it was last checked.
- Reference
- Upstage's flagship 102B-parameter large language model
- Last updated
- 23 July 2026
What the numbers mean
About this model
Solar Open 100B was published by Upstage, in the country recorded as Korea (Republic of), during December 2025. The publishing organisation is categorised as industry.
It works in the domain of Language, and is recorded as performing the task of language modeling/generation, 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
The training run consumed about 1.4 × 10²⁴ 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 19,700,000,000,000 tokens of text.
Its inclusion criterion: training cost.
Answers
Solar Open 100B — common questions
Solar Open 100B— how much compute was used to train it?
Training consumed around 1.4 × 10²⁴ 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.
Solar Open 100B— 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.
Solar Open 100B— is it open source?
No. Its weights have not been published, so it exists only as a service controlled by its owner.
Solar Open 100B— how many parameters does it have?
It has a parameter count of 102B. 102B, of which 12B active. 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.
Solar Open 100B— who created it?
It was published by Upstage, based in Korea (Republic of), an organisation categorised as industry.
Solar Open 100B— when was it released?
It was published in December 2025.
Solar Open 100B— what is it used for?
It works in the domain of Language, and is recorded as handling the task of language modeling/generation, Chat. These are the areas it was designed around; they describe intent rather than a hard boundary.
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.