Text Embedding 3 Large API
OpenAI's largest embedding model. Generates 3072-dimensional vectors. Best for semantic search, clustering, and classification at scale.
💰 Save up to 70% vs official OpenAI pricingText Embedding 3 Large — cheaper than the official OpenAI API
Access Text Embedding 3 Large through AI API Hub and pay less per token. Same OpenAI-compatible endpoint, lower cost.
Technical Specifications
| Provider | OpenAI |
| Model Family | Text Embedding 3 Large |
| Release Date | 2024-01 |
| Context Window | 8K |
| Max Output Tokens | 1 |
| Input Price | $0.13 / 1M tokens |
| Output Price | $0.13 / 1M tokens |
| Vision Support | No |
| Function Calling | No |
| JSON Mode | No |
| Streaming | No |
| Fine Tuning | Not Available |
| Status | Active ✓ |
Overview
Text Embedding 3 Large is OpenAI's current embedding model, released in 2024-01. OpenAI's largest embedding model. Generates 3072-dimensional vectors. Best for semantic search, clustering, and classification at scale.
For developers, the headline numbers are a 8K context window and up to 1 output tokens per response — enough headroom for highest quality embedding and 3072 dimensions without chunking your input. Priced at $0.13/1M input and $0.13/1M output, it sits in the budget tier — ideal for high-volume pipelines where token cost dominates.
On the capability side, Text Embedding 3 Large exposes 4 features: Embedding, Vector Search, Semantic Search, Classification. Note that fine-tuning isn't supported — you'll work with the base model. It's text-only, so route image or audio workloads elsewhere.
The practical appeal of routing Text Embedding 3 Large through AI API Hub is simplicity: one OpenAI-compatible endpoint, USDT & USDC payments, no credit card, and you're calling the API in under 30 seconds — just swap your base URL.
What Makes Text Embedding 3 Large Different
How Text Embedding 3 Large is used
Text Embedding 3 Large is used exclusively for vector embedding — you feed text in and get a fixed-length numeric vector back. Typical pipelines: semantic search (cosine similarity over stored vectors), deduplication, clustering, and as a retrieval layer for RAG. It doesn't generate text; pair it with a chat model for the generation step.
Pricing position within OpenAI
Text Embedding 3 Large sits in the middle of OpenAI's pricing at $0.13/1M input — 96% below the lineup average ($0.10 cheapest, $20.00 most expensive). 1 sibling cost less, 10 cost more. This mid-tier positioning makes it a sensible default when you're unsure which variant to pick.
Text Embedding 3 Large's role in the lineup
Within OpenAI's lineup, Text Embedding 3 Large is a mid-tier option — balanced between cost and capability. It's a standalone variant in its family. This makes it a safe default for production workloads where you're not sure which tier to pick.
Real-world use cases
Real-world deployments: semantic search engines (cosine similarity over stored vectors), RAG retrieval layers feeding a chat model, content deduplication pipelines, and recommendation systems. Teams pair Text Embedding 3 Large with a generation model — embeddings handle retrieval, the chat model handles synthesis.
vs sibling models
What makes Text Embedding 3 Large different from sibling models: compared to GPT-5.5 ($4.87/1M more expensive, 256K vs 8K context (larger)); GPT-5.4 ($2.37/1M more expensive, 256K vs 8K context (larger)); GPT-4.1 ($1.87/1M more expensive, 1M vs 8K context (larger)). Choose Text Embedding 3 Large when a balanced cost-to-capability ratio fits your workload.
API Examples
Python
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.apiyihe.org/v1"
)
response = client.chat.completions.create(
model="text-embedding-3-large",
messages=[
{"role": "user", "content": "Hello"}
]
)
print(response.choices[0].message.content)JavaScript / Node.js
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.API_KEY,
baseURL: "https://api.apiyihe.org/v1"
});
const response = await client.chat.completions.create({
model: "text-embedding-3-large",
messages: [
{ role: "user", content: "Hello" }
]
});
console.log(response.choices[0].message.content);cURL
curl https://api.apiyihe.org/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "text-embedding-3-large",
"messages": [
{"role": "user", "content": "Hello"}
]
}'Supported Features
| Vision / Image Input | ❌ Not Available |
| Audio / Voice Input | ❌ Not Available |
| Function Calling | ❌ Not Available |
| JSON Mode | ❌ Not Available |
| Streaming | ❌ Not Available |
| Fine-Tuning | ❌ Not Available |
| Multimodal | ❌ Not Available |
Benchmark Scores
| Benchmark | Score |
|---|---|
| MMLU | Not Publicly Available |
| GPQA | Not Publicly Available |
| SWE-Bench | Not Publicly Available |
| HumanEval | Not Publicly Available |
| GSM8K | Not Publicly Available |
| MATH | Not Publicly Available |
| MMMU | Not Publicly Available |
Pricing History
Text Embedding 3 Large was released in 2024-01 by OpenAI and is currently publicly available via AI API Hub.
Current Pricing: $0.13 per 1M input tokens · $0.13 per 1M output tokens. Pay-as-you-go with no minimum commitment.
Pricing Model: Token-based billing (pay per use). No subscription fees. No hidden costs.
💡 OpenAI occasionally updates pricing. AI API Hub reflects current pricing in real-time. All prices in USD. Pay with USDT or USDC — no currency conversion fees.
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Frequently Asked Questions
What is Text Embedding 3 Large?
Text Embedding 3 Large is OpenAI's current embedding model. OpenAI's largest embedding model. Generates 3072-dimensional vectors. Best for semantic search, clustering, and classification at scale. It offers a 8K context window and supports Embedding, Vector Search, Semantic Search. You can access it through AI API Hub using USDT or USDC — no credit card required.
How much does Text Embedding 3 Large cost?
Text Embedding 3 Large is priced at $0.13 per 1M input tokens and $0.13 per 1M output tokens, billed pay-as-you-go with no minimum. Through AI API Hub you can start with as little as $5 and scale from there.
Text Embedding 3 Large vs Claude Opus 4.8?
They're built for different jobs. Text Embedding 3 Large costs $0.13/1M input with a 8K window; Claude Opus 4.8 runs $5.00/1M input with 1M. Text Embedding 3 Large is the more cost-effective pick and still brings highest quality embedding. See the full side-by-side at /compare/text-embedding-3-large-vs-claude-opus-4.8/.
Text Embedding 3 Large context window?
Text Embedding 3 Large has a 8K context window, capable of processing up to 8,191 tokens in a single request. Maximum output tokens: 1.
Does Text Embedding 3 Large support function calling?
No, Text Embedding 3 Large does not natively support function calling. For function calling use cases, consider OpenAI's flagship models.
Is Text Embedding 3 Large multimodal?
No, Text Embedding 3 Large is a text-only model. For multimodal use cases, consider models with vision/audio capabilities.
Text Embedding 3 Large API rate limits?
Text Embedding 3 Large rate limits: 10K RPM. Higher tier plans offer increased throughput. For high-volume production use, consider OpenAI's faster variant models.
How to access Text Embedding 3 Large API?
Access Text Embedding 3 Large through AI API Hub: (1) Register at api.apiyihe.org/register?aff=8JZC, (2) Deposit USDT/USDC, (3) Get your API key instantly, (4) Use the OpenAI-compatible endpoint https://api.apiyihe.org/v1 with model name "text-embedding-3-large". Start building in under 30 seconds.