Solar Open 100B

Closed weights Upstage 102B parameters December 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
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

102B, of which 12B active

Training data
19,700,000,000,000 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 × 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 Korea (Republic of), in December 2025. The organisation is categorised as industry.

It works in Language, and is recorded as doing 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 describes the cost of creating it and has no bearing on how quickly it generates text.

It was trained on about 19,700,000,000,000 tokens of text.

Its inclusion criterion is training cost.

Answers

Solar Open 100B — common questions

01

How much compute was used to train Solar Open 100B?

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.

02

What GPU do I need to run Solar Open 100B?

None. Solar Open 100B 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.

03

Is Solar Open 100B open source?

No. Solar Open 100B has not had its weights published, so it exists only as a service controlled by its owner.

04

How many parameters does Solar Open 100B have?

Solar Open 100B has 102B parameters. 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.

05

Who created Solar Open 100B?

Solar Open 100B was published by Upstage, based in Korea (Republic of), categorised as industry.

06

When was Solar Open 100B released?

Solar Open 100B was published in December 2025.

07

What is Solar Open 100B used for?

Solar Open 100B 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.

Source

Original publication

Record last updated 23 July 2026

The other direction

Looking at it from the other side?

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