tsuzumi 7B upgrade 2024

Closed weights NTT Communication Science Laboratories 7B parameters April 2024

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
NTT Communication Science Laboratories
Organisation type
Industry
Country
Japan
Published
11 April 2024
Authors
Kyosuke Nishida

What it does

The problem areas the model was built for. A model can carry several of each.

Domain
Language, Multimodal, Vision
Task
Chat, Language modeling/generation, Document classification

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
7B

7B

Training data
1,000,000,000,000 tokens

1T+ from https://ntt-research.com/2024-upgrade-reality-tsuzumi/ 5:55

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
4.2 × 10²² FLOP

6ND = 6 * 7000000000 * 1000000000000 = 4.2e+22 (unknown number of epochs -> 'likely' confidence)

How it was established
Operation counting

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.

Reference
NTT's Large Language Model "tsuzumi" is Here!
Last updated
28 November 2025

What the numbers mean

What this model is

tsuzumi 7B upgrade 2024 was published by NTT Communication Science Laboratories, in the country recorded as Japan, during April 2024. The category the publisher falls under is industry.

It works in the domain of Language, Multimodal, Vision, and is recorded as performing the task of chat, Language modeling/generation, Document classification.

Its weights were never published, so it can only be reached through its provider. No graphics card changes that.

How it was trained

Training it took a computation budget of roughly 4.2 × 10²² 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 1,000,000,000,000 tokens of text.

Answers

tsuzumi 7B upgrade 2024 — common questions

01

tsuzumi 7B upgrade 2024— is it open source?

The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.

02

tsuzumi 7B upgrade 2024— how many parameters does it have?

It has a parameter count of 7B. 7B. 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.

03

tsuzumi 7B upgrade 2024— who created it?

It was published by NTT Communication Science Laboratories, based in Japan, an organisation categorised as industry.

04

tsuzumi 7B upgrade 2024— when was it released?

It was published in April 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

05

tsuzumi 7B upgrade 2024— what is it used for?

It works in the domain of Language, Multimodal, Vision, and is recorded as handling the task of chat, Language modeling/generation, Document classification. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.

06

tsuzumi 7B upgrade 2024— how much compute was used to train it?

Training consumed around 4.2 × 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.

07

tsuzumi 7B upgrade 2024— 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.

Source

Original publication

Record last updated 28 November 2025

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.