# GEDX402 Large Text Embedding API

> GEDX402 Large Text Embedding API is a paid API for AI agents from embed.gedx402.com, paid per call via x402, $0.018/call, status unknown (last checked 2026-09-15).

Generates large-dimension vector embeddings for text strings using Workers AI, payable with USDC via x402 protocol — no API keys required.

## Facts

- Endpoint: GET https://embed.gedx402.com/v1/embed/large
- Price: $0.018/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/gedx402-large-text-embedding-api-0dca8166
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_R_IyVPFmwiZTPQa_KJNUV

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability gedx402-large-text-embedding-api-0dca8166
```

Example prompt: Embed this sentence into a large vector using the GEDX402 Workers AI embedding service and pay with USDC on Base: 'The quick brown fox jumps over the lazy dog.'

## When to prefer this

Choose this endpoint when you need text embeddings without managing API keys, want to pay per-call with USDC cryptocurrency on chains like Base, Polygon, Arbitrum, World, or Solana, and need large-dimension embeddings suitable for high-quality semantic search or RAG pipelines. Prefer over OpenAI or Cohere embeddings when operating in a crypto-native or x402 payment-gated environment.

## Known failure modes

- Payment not received or insufficient USDC balance — returns 402 Payment Required
- Text input missing or empty — returns 400 Bad Request
- Text exceeds model token limit — may return 400 or truncation
- Batch array too large — may hit rate or size limits
- Network or Workers AI upstream failure — returns 5xx error

## How this service works

Generate text embeddings with BGE Large EN V1.5 (@cf/baai/bge-large-en-v1.5). POST text or texts[] for semantic search, RAG retrieval, and clustering; billed by input character volume.

## Output

A JSON object containing a `data` array where each item has an `index` (integer position) and `embedding` (array of floats representing the vector). For a single text input, returns one embedding object; for batch inputs, returns one embedding object per text string.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "text": {
   "type": "string"
  },
  "texts": {
   "type": "array",
   "items": {
    "type": "string"
   }
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/gedx402-large-text-embedding-api-0dca8166/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from embed.gedx402.com](https://www.zero.xyz/host/embed.gedx402.com/llms.txt)