# ARBITER Embedding API

> ARBITER Embedding API is a paid API for AI agents from api.grip.fyi, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-14).

Generates deterministic vector embeddings for input text strings, suitable for memory storage, semantic indexing, retrieval, and clustering tasks.

## Facts

- Endpoint: POST https://api.grip.fyi/v1/embed
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/arbiter-embedding-api-bc236013
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_vboad1MS-Wcx7qHdzDd8R

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 arbiter-embedding-api-bc236013 -d '<json body>'
```

Example prompt: Embed these five product description strings into deterministic vector representations so I can index them for semantic search: 'noise-cancelling headphones', 'wireless earbuds', 'studio monitor speakers', 'bluetooth soundbar', 'portable DAC amplifier'.

## When to prefer this

Choose this endpoint when you need deterministic, reproducible embeddings — meaning the same input always produces the same vector — for use cases like agent memory, cross-system semantic alignment, deduplication, or coherence measurement. Prefer it over non-deterministic embedding services when consistency across runs is critical.

## Known failure modes

- Empty texts array returns validation error
- Strings exceeding model token limit may be truncated or rejected
- Network timeout on large batches
- Non-UTF-8 or malformed strings may cause processing errors
- Rate limiting if too many calls in short succession

## How this service works

Create deterministic persistent machine representations for memory, indexing, retrieval, clustering, reuse, cross-system meaning, and downstream coherence measurement.

## Output

Returns deterministic vector embeddings for each input string — fixed-length numerical representations that can be stored, compared via cosine similarity, clustered, or indexed in a vector database for downstream retrieval and coherence measurement tasks.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "texts": {
   "type": "array",
   "items": {
    "type": "string"
   },
   "minItems": 1,
   "description": "Strings to represent in the deterministic ARBITER field."
  },
  "use_freq": {
   "type": "boolean",
   "default": true
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/arbiter-embedding-api-bc236013/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from api.grip.fyi](https://www.zero.xyz/host/api.grip.fyi/llms.txt)