OpenAI TI7 DOTA 1v1

Closed weights OpenAI August 2017

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
OpenAI
Organisation type
Industry
Country
United States of America
Published
11 August 2017

What it does

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

Domain
Games
Task
Dota 2

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.

Training data
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
6 × 10²⁰ FLOP

Extracted from AI and Compute (https://openai.com/blog/ai-and-compute/) charts by using https://automeris.io/WebPlotDigitizer/.

How it was established
Third-party estimation

How it is classified

Labels the source dataset applies when tracking notable models, and how confident it is in the entry.

Frontier model
Yes
Why it is tracked
Historical significance,SOTA improvement
Record confidence
Confident

Sources

Where this record came from and when it was last checked.

Reference
Dota 2
Last updated
28 November 2025

What the numbers mean

About this model

OpenAI TI7 DOTA 1v1 was published by OpenAI, in United States of America, in August 2017. The organisation is categorised as industry.

It works in Games, and is recorded as doing dota 2.

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

Training and provenance

Producing it required around 6 × 10²⁰ FLOP of arithmetic, which is a statement about the training budget rather than about inference.

It is tracked in the underlying dataset for one reason in particular: historical significance,SOTA improvement.

Answers

OpenAI TI7 DOTA 1v1 — common questions

01

When was OpenAI TI7 DOTA 1v1 released?

OpenAI TI7 DOTA 1v1 was published in August 2017. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

02

What is OpenAI TI7 DOTA 1v1 used for?

OpenAI TI7 DOTA 1v1 works in Games, and is recorded as handling dota 2. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.

03

How much compute was used to train OpenAI TI7 DOTA 1v1?

Around 6 × 10²⁰ 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.

04

What GPU do I need to run OpenAI TI7 DOTA 1v1?

None. OpenAI TI7 DOTA 1v1 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.

05

Is OpenAI TI7 DOTA 1v1 open source?

The licensing for OpenAI TI7 DOTA 1v1 was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.

06

How many parameters does OpenAI TI7 DOTA 1v1 have?

No parameter count has been published for OpenAI TI7 DOTA 1v1, which is why no memory or speed figure appears on this page.

07

Who created OpenAI TI7 DOTA 1v1?

OpenAI TI7 DOTA 1v1 was published by OpenAI, based in United States of America, categorised as industry.

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.