PolySphere-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
- AI inside
- Organisation type
- Industry
- Country
- Japan
- Published
- 8 June 2023
- Authors
- AI Inside
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Chat, Language modeling/generation, Japanese language modeling
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
- 14B
- Training data
- tokens
14B from https://inside.ai/en/news/2023/06/08/aiinside-xresearch/
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
- Unreleased
- 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
- AI inside Establishes “XResearch” for R&D and Social Implementation of Generative AI and LLM, Providing the Alpha Version of a 14 Billion-Parameter Japanese LLM Service
- Last updated
- 28 November 2025
What the numbers mean
Background
PolySphere-1 was published by AI inside, in Japan, in June 2023. It comes out of industry.
It works in Language, and is recorded as doing chat, Language modeling/generation, Japanese language modeling.
This is a closed model: the trained values stayed with whoever produced them, and there is no local version to run.
Answers
PolySphere-1 — common questions
Who created PolySphere-1?
PolySphere-1 was published by AI inside, based in Japan, categorised as industry.
When was PolySphere-1 released?
PolySphere-1 was published in June 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 PolySphere-1 used for?
PolySphere-1 works in Language, and is recorded as handling chat, Language modeling/generation, Japanese language modeling. These are the areas it was designed around; they describe intent rather than a hard boundary.
What GPU do I need to run PolySphere-1?
None. PolySphere-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 PolySphere-1 open source?
No. PolySphere-1 has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does PolySphere-1 have?
PolySphere-1 has 14B parameters. 14B from https://inside.ai/en/news/2023/06/08/aiinside-xresearch/. 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.