OpenAI text-embedding-3-large

Name: OpenAI text-embedding-3-large
Brand: OpenAI
SKU: text-embedding-3-large
Price: 0.156 USD
Availability: InStock

InnfellingarTiltækt

eftir OpenAItext-embedding-3-large

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.

Prófaðu það Fáðu API-lykil Bera saman

Verð: 0,156 USD/1M inn
Samhengi: 8.191 tákn
Inntak → úttak: Texti → Vigur
Þróunaraðili: OpenAI
Uppfært: 23. september 2026

Leiksvæði

Prófaðu OpenAI text-embedding-3-large

Inntak og úttak

0,156 USD/1M inn

Inntak

0 / 32.000

Bera saman við (valfrjálst)

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Niðurstaða

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Um OpenAI text-embedding-3-large

StuttlegaFrá og með 23. september 2026

OpenAI text-embedding-3-large er módel frá OpenAI í flokknum Innfellingar. Á Railwail kostar OpenAI text-embedding-3-large 0,156 USD / 1M inntakstákn. Samhengisgluggi geymir 8.191 tákn.

text-embedding-3-large is OpenAI's most capable third-generation embedding model. It produces 3072-dim embeddings by default and, like the small variant, supports the dimensions parameter for Matryoshka-style truncation so you can store shorter vectors when needed. It leads OpenAI's lineup on the MTEB English benchmark and on the multilingual MIRACL retrieval benchmark, making it the pick when embedding quality is the priority over price. Use it for high-recall semantic search, deduplication and reranking-style retrieval. Accepts a single string or a batch per request.

Bakgrunnur

Um OpenAI

Stofnað 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 capped-profit OpenAI LP in 2019. The embedding model family started with text-embedding-ada-001 in 2021, was unified into text-embedding-ada-002 in December 2022 (still the most-used embedding model on Earth at one point) and replaced in January 2024 by text-embedding-3-small and text-embedding-3-large. The v3 release was OpenAI's first to support Matryoshka-style dimension reduction (sale of arbitrary 256-3072 dim vectors from the same model) and beat ada-002 by 20+ percentage points on the MIRACL multilingual retrieval benchmark while costing roughly the same.

Heimsækja OpenAI

Arkitektúr

Transformer bi-encoder with Matryoshka representation learning

OpenAI text-embedding-3-large is the flagship embedding model in the v3 generation. It produces 3,072-dimensional vectors by default with full Matryoshka representation support, so callers can request any dimension between 256 and 3,072 in the API and OpenAI will truncate-and-renormalise without re-running the model. The model accepts up to 8,191 tokens per input and was trained with a contrastive retrieval objective on a curated multilingual web corpus, including search-query/document pairs and large-scale instruction-tuned pairs. It scores 64.6% on MTEB and 54.9% on MIRACL multilingual retrieval, a step up from 61.0% / 31.4% for ada-002. Pricing is $0.00013 per 1k tokens. Output vectors are L2-normalised. Like all OpenAI models the system is closed-source and hosted only. OpenAI has not published a technical paper for the v3 family beyond a launch blog.

Breytur: Undisclosed
Samhengi: 8.191 tákn

Geta

3,072-dim vectors with Matryoshka truncation to any 256-3072 size
8,191-token context window for long-document embedding
Multilingual coverage across 100+ languages
State-of-the-art MIRACL multilingual retrieval (~55%)
L2-normalised vectors with cosine similarity
Drop-in upgrade from ada-002 via the same /embeddings endpoint
Best for: production RAG, multilingual search, retrieval-heavy SaaS

Þjálfun og leyfi

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

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

Öryggispróf: Embeddings are not subject to content-filter constraints; OpenAI publishes general bias and fairness statements for the embeddings endpoint.

Þekkt takmörk

Closed weights, hosted only
Cannot fine-tune the model
3,072-dim full vectors are storage-heavy without truncation
Worse-than-Cohere v3 on some low-resource languages
8,191-token cap may force chunking for very long documents

Rannsókargreinar

Verðlagning

Verð í Bandaríkjadölum. Notkun er rukkuð frá fyrirframgreiddum inneign.

Inntak	0,156 USD / 1M tákn

Reikningsfærðir eru tákn sem hver beiðni notar í raun.
1 inneign = 0,01 USD

Kostnaðarreiknir

Verðreiknir

Inntakstákn

/ beiðni

Úttakstákn

/ beiðni

Beiðnir

Samtals

0,02 USD

2 inneign

Fyrir hverja beiðni

0,0002 USD · 0,02 inneign

Hver beiðni er námunduð upp í 0,01 inneign.

API

Kallaðu OpenAI text-embedding-3-large með Railwail API-lyklinum þínum. Notaðu þessa módel-auðkenningu í beiðninni:

text-embedding-3-largeAPI-skjöl Fáðu API-lykil

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

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

Stilltu lykil þinn sem RAILWAIL_API_KEYBúa til API-lykil

Forskriftir

Módel-auðkenni: text-embedding-3-large
Þróunaraðili: OpenAI
Flokkur: Innfellingar
Inntak: Texti
Úttak: Vigur
Samhengisglugginn: 8.191 tákn
Reikningur: Eftir notkun (tókar eða GPU-tími)
Stærð módels: Undisclosed
Leyfi: Proprietary commercial API. Generated embeddings may be stored and used commercially under the OpenAI Usage Policy.
Vörulistafærsla uppfærð: 23. september 2026

Inntaksbreytur

Inntak og stillingar úr inntakskerfi módelsins. Dæmið í API-hlutanum sýnir hverjar þeirra API samþykkir.

BreytuTegundSjálfgefiðLeyfðir gildir

inputnauðsynlegt
Text to embed (single string or array of strings)
Tegund: Texti
Sjálfgefið: –
Leyfðir gildir: allt að 32.000 stafir
dimensions
Tegund: Heiltala
Sjálfgefið: 3072
Leyfðir gildir: 256 til 3.072
encoding_format
Tegund: Val
Sjálfgefið: float
Leyfðir gildir: float eða base64

Merki

openai
embedding
retrieval
rag
matryoshka
multilingual

Dæmi um leiðsögn

Dæmi úr Railwail-vörulistanum. Þau voru ekki mynduð lifandi á þessari síðu.

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Notkunartilvik

Það sem það er notað fyrir

Production RAG for ChatGPT-style assistants
Multilingual enterprise search
Semantic deduplication and clustering at scale
Recommendation systems based on text similarity
Embeddings for downstream classification tasks

Tengdar leiðbeiningar

Embedding Models for Search & Science

Öll módel í Innfellingar

Algengar spurningar

Hvað er OpenAI text-embedding-3-large?

OpenAI text-embedding-3-large er módel frá OpenAI í flokknum Innfellingar. Á Railwail geturðu kallað það með API-lykli í gegnum Railwail API.

Hvað kostar OpenAI text-embedding-3-large á Railwail?

Á Railwail kostar OpenAI text-embedding-3-large 0,156 USD / 1M inntakstákn. Þér er rukkað fyrir það sem hver beiðni notar í raun. Notkun er greidd úr fyrirframgreiddum inneign; 1 inneign jafngildir 0,01 USD.

Hversu stór er samhengisgluggi OpenAI text-embedding-3-large?

Samhengisgluggi OpenAI text-embedding-3-large geymir 8.191 tákn.

Hversu hratt er OpenAI text-embedding-3-large?

Það eru ekki nóg mældar keyrslur af OpenAI text-embedding-3-large á Railwail ennþá til að tilgreina keyrslutíma. Það fer eftir inntakinu, stillingum og álagi hjá veitandanum.

Er OpenAI text-embedding-3-large betra en OpenAI text-embedding-3-small?

Það fer eftir verkefninu. OpenAI text-embedding-3-large (OpenAI) og OpenAI text-embedding-3-small (OpenAI) eru bæði módel í flokknum Innfellingar. Samanburðarsíðan sýnir verð og forskriftir þeirra hlið við hlið.

Bera saman OpenAI text-embedding-3-large og OpenAI text-embedding-3-small

Hvernig nota ég OpenAI text-embedding-3-large í gegnum API?

Búðu til Railwail API-lykil og sendu beiðni þína með módel-auðkenninu text-embedding-3-large. Kóðadæmi fyrir curl, Python og JavaScript eru í API-hlutanum á þessari síðu.

Sambærileg módel

Öll í þessum flokki

OpenAI text-embedding-3-smallOpenAI
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.
0,024 USD/1M inn
85 % ódýrara á einingu
Bera OpenAI text-embedding-3-large og OpenAI text-embedding-3-small saman

Notaðu OpenAI text-embedding-3-large í gegnum API

Einn API-lykil fyrir öll módel á Railwail. Notkun er rukkuð frá fyrirframgreiddum inneign, 1 inneign = 0,01 USD.

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