OpenAI: Text Embedding 3 Large
Embeddingopenai/text-embedding-3-largeText Embedding 3 Large is OpenAI's most capable embedding model, strong on both English and non-English text. It turns text into numerical vectors whose distances measure how closely two pieces of text are related, which makes it a fit for search, clustering, recommendations, anomaly detection, and classification. Input limit: 8K tokens per request. At $0.13/M input tokens it stays affordable for large-scale corpus indexing as well as query-time embedding. Accessible via the OpenAI-compatible protocol through Ofox.
Context Window
8K
Max Output Tokens
8K
Released
2025-10-30
Available Providers
Azure
Supported Protocols
openai
Providers
Azure
-20%Input Tokens
$0.104/M
$0.13/M
Output Tokens
$0/M
Web Search
$0.035/R
Protocols
openai
/v1/embeddingsCode Examples
from openai import OpenAIclient = OpenAI(base_url="https://api.ofox.ai/v1",api_key="YOUR_OFOX_API_KEY",)response = client.embeddings.create(model="openai/text-embedding-3-large",input="Hello, world!",)print(response.data[0].embedding[:5])
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Frequently Asked Questions
OpenAI: Text Embedding 3 Large on Ofox.ai costs $0.13/M per million input tokens and $0 per million output tokens. Pay-as-you-go, no monthly fees.
OpenAI: Text Embedding 3 Large supports a context window of 8K tokens with max output of 8K tokens, allowing you to process large documents and maintain long conversations.
Simply set your base URL to https://api.ofox.ai/v1 and use your Ofox API key. The API is OpenAI-compatible โ just change the base URL and API key in your existing code.