Imagegpt Large
OpenAI's ImageGPT Large is a transformer decoder model pretrained on 14 million images from ImageNet ILSVRC 2012 in a self-supervised fashion, learning to predict the next pixel value given previous ones. It is genuinely best at learning an inner representation of images for downstream tasks such as feature extraction and unconditional image generation.
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1K
Max Output
1K
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Frequently asked questions about Imagegpt Large
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Imagegpt Large advertises a context window of 1,024 tokens, with a maximum output of 1,024 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Imagegpt Large is an open-weight model released under the Apache 2.0 license, so the weights can be downloaded and self-hosted within that license's terms.
Imagegpt Large accepts Image and produces Image and Embedding. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Imagegpt Large is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Imagegpt Large is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
OpenAI has not published a parameter count for Imagegpt Large, so the catalog cannot estimate its memory footprint. The capacity planner can size it from a parameter count you supply.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Aug 28, 2026
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