GPT-4 Turbo (Nov 2023)
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
- 6 November 2023
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Multimodal, Vision, Language, Image generation
- Task
- Chat, Language modeling/generation, Image generation, Speech synthesis, Table tasks, Visual question answering, Image captioning
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.
- How it was established
- Benchmarks
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
- Training code
- Unreleased
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Frontier model
- Yes
- Foundation model
- Yes
- Likely above 10²³ FLOP
- Yes
- Why it is tracked
- SOTA improvement
- Record confidence
- Unknown
"More capable" than GPT-4 according to OpenAI, with larger context window
Sources
Where this record came from and when it was last checked.
- Reference
- New models and developer products announced at DevDay
- Last updated
- 11 February 2026
What the numbers mean
Where it came from
GPT-4 Turbo (Nov 2023) was published by OpenAI, in United States of America, in November 2023. It comes out of industry.
It works in Multimodal, Vision, Language, Image generation, and is recorded as doing chat, Language modeling/generation, Image generation, Speech synthesis, Table tasks, Visual question answering, Image captioning.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Training and provenance
It is tracked in the underlying dataset for one reason in particular: sOTA improvement.
Answers
GPT-4 Turbo (Nov 2023) — common questions
How many parameters does GPT-4 Turbo (Nov 2023) have?
No parameter count has been published for GPT-4 Turbo (Nov 2023), which is why no memory or speed figure appears on this page.
Who created GPT-4 Turbo (Nov 2023)?
GPT-4 Turbo (Nov 2023) was published by OpenAI, based in United States of America, categorised as industry.
When was GPT-4 Turbo (Nov 2023) released?
GPT-4 Turbo (Nov 2023) was published in November 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 GPT-4 Turbo (Nov 2023) used for?
GPT-4 Turbo (Nov 2023) works in Multimodal, Vision, Language, Image generation, and is recorded as handling chat, Language modeling/generation, Image generation, Speech synthesis, Table tasks, Visual question answering, Image captioning. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
What GPU do I need to run GPT-4 Turbo (Nov 2023)?
None. GPT-4 Turbo (Nov 2023) 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 GPT-4 Turbo (Nov 2023) open source?
No. GPT-4 Turbo (Nov 2023) has not had its weights published, so it exists only as a service controlled by its owner.
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.