OpenAI Text Embeddings
OpenAIOpenAI's general-purpose text embedding models, text-embedding-3-small and text-embedding-3-large, reached only through the /v1/embeddings endpoint. Both accept 8,192 tokens, default to 1,536 and 3,072 dimensions, and were trained with Matryoshka-style shortening so a caller can trade dimensions for storage through the `dimensions` parameter.
Still the January 2024 generation as of 2026-09-11: OpenAI's own embeddings guide lists text-embedding-3-small, text-embedding-3-large and the legacy text-embedding-ada-002 and nothing newer, so there is no text-embedding-4. No weights, corpus or training code are published, which is why openness stops at the ladder's first rule. Verified 2026-09-11 via the OpenAI embeddings guide and the Azure AI Foundry model list.
Openness
1 high confidence- weights
- closed(no checkpoint distributed
- data
- closed(training corpus neither released nor described)
- code
- closed(no training or inference implementation
- license
- proprietary(hosted API under OpenAI business terms
API-only. The guide documents an endpoint, a dimensions parameter and a price, and nothing that can be downloaded, so the ladder's first rule fires ahead of any license question.
- https://developers.openai.com/api/docs/guides/embeddings recorded 2026-09-11
Documents text-embedding-3-small and text-embedding-3-large as endpoint calls with an 8,192-token limit and a `dimensions` parameter; the page offers no weight download, no corpus description and no training code, and names no successor model.
Adoption
4 medium confidenceNo artifact to count and no call volume published. The level rests on distribution and on the models' standing as the industry's default baseline: Microsoft resells both SKUs directly through Azure AI Foundry, and every rival's evaluation benchmarks against OpenAI v3 Large as the reference point rather than against each other. Directional, so confidence stops at medium.
- https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models recorded 2026-09-11
Azure AI Foundry's models-sold-directly-by-Azure list carries text-embedding-3-large and text-embedding-3-small, so the models are resold by Microsoft as well as served by OpenAI.
- https://blog.voyageai.com/2026/01/15/voyage-4/ recorded 2026-09-11
Voyage's RTEB evaluation picks 'OpenAI v3 Large' as one of three external reference models to measure against, alongside Gemini Embedding 001 and Cohere Embed v4.
Capability
3 high confidenceRung 3, solid workhorse: a superseded generation still carrying credible published numbers and enormous everyday use. It is two and a half years old, short-context by 2026 standards at 8,192 tokens, text-only, and the largest measured gap in Voyage's own RTEB comparison. That is the rung's definition rather than a demotion.
- https://developers.openai.com/api/docs/guides/embeddings recorded 2026-09-11
Model table: text-embedding-3-small 62.3%, text-embedding-3-large 64.6%, text-embedding-ada-002 61.0% on 'Performance on MTEB eval', max input 8192 for all three.
- https://blog.voyageai.com/2026/01/15/voyage-4/ recorded 2026-09-11
'voyage-4-large is the top-performing model, surpassing voyage-4, voyage-4-lite, Gemini Embedding 001, Cohere Embed v4, and OpenAI v3 Large by an average of 1.87%, 4.80%, 3.87%, 8.20%, and 14.05%, respectively' over all 29 RTEB datasets.
Verified 2026-09-11