agent402.tools Text Embedding (Large, 3072-dim) is a paid API for AI agents from agent402.tools, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-13).
Generates a 3072-dimensional text embedding vector using OpenAI text-embedding-3-large, ideal for semantic search, RAG, and clustering — no API key needed, pay-per-call via x402.
Generate a text embedding vector using OpenAI text-embedding-3-large (3072 dimensions). Higher accuracy than the small model. Ideal for semantic search, RAG, and clustering. No API key needed; pay per call via x402. Text capped at 32k chars.
A 3072-dimensional floating-point vector representing the semantic content of the input text, produced by OpenAI's text-embedding-3-large model. The vector can be used directly in cosine similarity comparisons, vector database indexing, clustering, or RAG retrieval pipelines.
POSThttps://agent402.tools/api/embed-largeChoose this endpoint when you need the highest-quality embeddings from OpenAI's text-embedding-3-large model (3072 dimensions) and either lack an OpenAI API key or prefer a simple pay-per-call model via x402. Prefer over the small variant when accuracy is critical — e.g., for RAG systems where retrieval quality matters, or clustering tasks requiring fine-grained semantic distinctions. The $0.01 USDC per call pricing is straightforward for low-to-medium volume usage.
| Field | Type | Description |
|---|---|---|
| text | string | Text to embed (max 32,000 chars) |
{
"type": "json",
"example": {
"model": "text-embedding-3-large",
"usage": {
"total_tokens": 12
},
"provider": "openai",
"embedding": [
0.0023,
-0.0091,
0.0152
],
"dimensions": 3072
}
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