OpenAI text-embedding-3-small

Name: OpenAI text-embedding-3-small
Brand: OpenAI
SKU: text-embedding-3-small
Price: 0.024 USD
Availability: InStock

EmbeddingsDostupno

od OpenAItext-embedding-3-small

OpenAI's small, low-cost embedding model. Returns 1536-dim vectors by default and supports shortening output dimensions via the dimensions parameter without retraining. Replaced text-embedding-ada-002 with better retrieval quality at a fraction of the price, and is the default choice for general-purpose semantic search and RAG.

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Cijena: 0,024 US$/1M in
Kontekst: 8.191 tokena
Ulaz → izlaz: Tekst → Vektor
Razvojni inženjer: OpenAI
Ažurirano: 23. septembar 2026.

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Unos i rezultat

0,024 US$/1M in

Unos

0 / 32.000

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O OpenAI text-embedding-3-small

UkratkoStanje: 23. septembar 2026.

OpenAI text-embedding-3-small je model od OpenAI iz kategorije Embeddings. Na Railwailu, OpenAI text-embedding-3-small košta 0,024 US$ / 1M input tokena. Kontekstni prozor sadrži 8.191 tokena.

text-embedding-3-small is the cheaper of OpenAI's third-generation embedding models. It outputs 1536-dim embeddings by default but supports the dimensions parameter, which uses Matryoshka-style truncation so you can request shorter vectors (for example 512 dims) and trade a small amount of accuracy for lower storage and faster similarity search. It scores higher than the older ada-002 on the MTEB benchmark while costing significantly less, which makes it the common default for production retrieval, clustering and classification pipelines. Accepts a single string or a batch of strings per request.

Pozadina

O OpenAI

Osnovano 2015 · San Francisco, California, USA

OpenAI was founded in December 2015 by Sam Altman, Elon Musk, Greg Brockman, Ilya Sutskever, Wojciech Zaremba and John Schulman and restructured to a capped-profit company in 2019. The embedding line started with text-embedding-ada-001 (2021), was unified into ada-002 (December 2022) and replaced in January 2024 by the v3 generation. text-embedding-3-small is the smaller, cheaper sibling of text-embedding-3-large: it beats ada-002 by ~5 points on MTEB at one fifth the price ($0.00002 per 1k tokens). Together with the large variant it was the first OpenAI embedding model to support Matryoshka-style dimension shortening, allowing callers to choose any vector size between 256 and 1,536 without retraining or quality drop.

Posjetite OpenAI

Arhitektura

Transformer bi-encoder with Matryoshka representation learning

OpenAI text-embedding-3-small is the entry-level embedding model in the v3 generation. It produces 1,536-dimensional vectors by default and supports the same Matryoshka shortening as the large variant, so callers can request any dimension between 256 and 1,536 in the API and OpenAI will truncate-and-renormalise on the fly. Maximum input length is 8,191 tokens. Training used a contrastive retrieval objective on a curated multilingual web corpus including search-query/document pairs. The model scores around 62.3% MTEB and 44.0% MIRACL multilingual retrieval, a clear step up from 61.0% / 31.4% for ada-002, while being roughly five times cheaper and faster. It is positioned as the default embedding model for cost-sensitive production RAG and large-scale search. Like all OpenAI models the system is closed-source and hosted only.

Parametri: Undisclosed (smaller than text-embedding-3-large)
Kontekst: 8.191 tokena

Mogućnosti

1,536-dim vectors with Matryoshka truncation to any 256-1,536 size
8,191-token context window for long-document embedding
Multilingual coverage across 100+ languages
$0.00002 per 1k tokens (~5x cheaper than text-embedding-3-large)
Drop-in upgrade from ada-002 via the same /embeddings endpoint
L2-normalised vectors with cosine similarity
Best for: cost-sensitive RAG, large-scale search, embeddings at high QPS

Obuka i licenca

Not disclosed. OpenAI describes a 'curated multilingual web corpus' with search-query/document pairs.

Licenca: Proprietary commercial API. Generated embeddings may be stored and used commercially under the OpenAI Usage Policy.

Testiranje sigurnosti: Embeddings are not subject to content-filter constraints; OpenAI publishes general bias and fairness statements.

Poznata ograničenja

Closed weights, hosted only
Cannot fine-tune the model
Lower MTEB / MIRACL scores than text-embedding-3-large
Multilingual quality below Cohere v3 for some low-resource languages
8,191-token cap may force chunking for long documents

Znanstveni članci

Cijene

Cijene u USD-u. Korištenje se naplaćuje iz unaprijed plaćenih kredita.

Ulaz	0,024 US$ / 1M tokena

Naplaćuje se prema tokenima koje svaki zahtjev zapravo koristi.
1 kredit = 0,01 US$

Kalkulator troškova

Kalkulator cijena

Ulazni tokeni

/ zahtjev

Izlazni tokeni

/ zahtjev

Zahtjevi

Ukupno

0,01 US$

1 kredita

Po zahtjevu

0,0001 US$ · 0,01 kredita

Svaki zahtjev se zaokružuje na 0,01 kredita.

API

Pozovi OpenAI text-embedding-3-small sa svojim Railwail API ključem. Koristi ovaj ID modela u zahtjevu:

text-embedding-3-smallPogledaj API dokumentaciju Dobij API ključ

curl https://railwail.com/api/v1/embeddings \
  -H "Authorization: Bearer $RAILWAIL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-3-small",
    "input": "The quick brown fox"
  }'

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["RAILWAIL_API_KEY"],
    base_url="https://railwail.com/api/v1",
)

res = client.embeddings.create(
    model="text-embedding-3-small",
    input="The quick brown fox",
)

print(len(res.data[0].embedding))

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.RAILWAIL_API_KEY,
  baseURL: "https://railwail.com/api/v1",
});

const res = await client.embeddings.create({
  model: "text-embedding-3-small",
  input: "The quick brown fox"
});

console.log(res.data[0].embedding.length);

Postavite ključ kao RAILWAIL_API_KEYKreiraj API ključ

Specifikacije

ID modela: text-embedding-3-small
Razvojni inženjer: OpenAI
Kategorija: Embeddings
Ulaz: Tekst
Izlaz: Vektor
Kontekstni prozor: 8.191 tokena
Naplata: Po potrošnji (tokeni ili GPU vrijeme)
Veličina modela: Undisclosed (smaller than text-embedding-3-large)
Licenca: Proprietary commercial API. Generated embeddings may be stored and used commercially under the OpenAI Usage Policy.
Katalog ažuriran: 23. septembar 2026.

Parametri ulaza

Ulazi i postavke iz sheme ulaza modela. Primjer u odjeljku API pokazuje koje od njih API prihvaća.

ParametarTipZadanoDozvoljene vrijednosti

inputobavezno
Text to embed (single string or array of strings)
Tip: Tekst
Zadano: –
Dozvoljene vrijednosti: do 32.000 znakova
dimensions
Tip: Cijeli broj
Zadano: 1536
Dozvoljene vrijednosti: 64 do 1.536
encoding_format
Tip: Izbor
Zadano: float
Dozvoljene vrijednosti: float ili base64

Oznake

openai
embedding
retrieval
rag
matryoshka
general

Primjer promptova

Primjeri iz Railwail kataloga. Nisu generirani uživo na ovoj stranici.

Semantic Search
How to deploy a Node.js app to production
Document Clustering
Machine learning model training techniques

Primjena

Za što se koristi

Cost-sensitive production RAG
Large-scale semantic search across millions of documents
Embeddings for high-QPS personalisation pipelines
Clustering and topic discovery at low cost
Embeddings for downstream classification

Povezani vodiči

Embedding Models for Search & Science

Svi modeli: Embeddings

Često postavljana pitanja

Što je OpenAI text-embedding-3-small?

OpenAI text-embedding-3-small je model od OpenAI iz kategorije Embeddings. Na Railwailu ga možete pozvati s API ključem kroz Railwail API.

Koliko stoji OpenAI text-embedding-3-small na Railwailu?

Na Railwailu, OpenAI text-embedding-3-small košta 0,024 US$ / 1M input tokena. Naplaćuje se ono što svaki zahtjev zapravo koristi. Korištenje se plaća iz unaprijed kupljenih kredita; 1 kredit jednaka je 0,01 US$.

Koliki je kontekstni prozor od OpenAI text-embedding-3-small?

Kontekstni prozor od OpenAI text-embedding-3-small sadrži 8.191 tokena.

Koliko je brz OpenAI text-embedding-3-small?

Za OpenAI text-embedding-3-small na Railwailu još nema dovoljno izmjerenih pokretanja da bi se navedlo vrijeme izvršavanja. Ovisi o unošenju, postavkama i opterećenju kod pružatelja.

Je li OpenAI text-embedding-3-small bolji od OpenAI text-embedding-3-large?

To ovisi o zadatku. OpenAI text-embedding-3-small (OpenAI) i OpenAI text-embedding-3-large (OpenAI) su oba modela iz kategorije Embeddings. Stranica za usporedbu prikazuje njihove cijene i specifikacije usporedno.

Usporedi OpenAI text-embedding-3-small i OpenAI text-embedding-3-large

Kako koristim OpenAI text-embedding-3-small kroz API?

Kreiraj Railwail API ključ i pošalji svoj zahtjev s ID-om modela text-embedding-3-small. Primjeri koda za curl, Python i JavaScript nalaze se u odjeljku API na ovoj stranici.

Usporedivi modeli

Svi u ovoj kategoriji

OpenAI text-embedding-3-largeOpenAI
OpenAI's highest-quality embedding model. Returns 3072-dim vectors by default and supports reducing dimensions via the dimensions parameter. Outperforms text-embedding-3-small and the older ada-002 on MTEB and multilingual MIRACL retrieval benchmarks, for cases where accuracy matters more than cost.
0,156 US$/1M in
550 % skupnije po jedinici
Usporedi OpenAI text-embedding-3-small i OpenAI text-embedding-3-large

Koristi OpenAI text-embedding-3-small preko API-ja

Jedan API ključ za sve modele na Railwailu. Korištenje se naplaćuje iz unaprijed plaćenih kredita, 1 kredit = 0,01 US$.

Dobij API ključ Pogledaj sve modele