OpenAIText Embedding 3 Small
OpenAI's Text Embedding 3 Small is a proprietary text embedding model capable of generating embeddings from input text. It is genuinely best at creating vector representations of text, leveraging its context window of up to 8,191 tokens to capture nuanced semantic relationships.
Input
Output
Context
8K
Max Output
n/a
Parameters
-
Technical Specifications
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Output Modalities
Capabilities
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Frequently asked questions about Text Embedding 3 Small
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Text Embedding 3 Small advertises a context window of 8,191 tokens. The figure is the creator's published maximum; a given provider may serve less, and the gateway routes on what each provider actually serves.
No. Text Embedding 3 Small is a proprietary model (license: Proprietary): its weights are not distributed, and it runs only through OpenAI's own API or a provider licensed to serve it.
Text Embedding 3 Small accepts Text and produces 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 Text Embedding 3 Small 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; Text Embedding 3 Small 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.
Text Embedding 3 Small cannot be self-hosted: its weights are not distributed. It is used through an API, either OpenAI's own or the Inferbase gateway where it is served.
Fields collected from public registries, provider APIs and benchmark publishers, each tagged with its source.
Last updated: Oct 13, 2026
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