embed

Convert text into a 768-dimension embedding vector (nomic-embed-text) for semantic search, RAG retrieval, clustering, deduplication or similarity scoring.

Convert text into a 768-dimension embedding vector (nomic-embed-text) for semantic search, RAG retrieval, clustering, deduplication or similarity scoring. POST JSON {"input": string}, up to 3000 characters; returns {embedding: number[768], model, dimensions, elapsed_ms}. One text per call; English works best.

UNRATEDListed

Overview

Grade?

UNRATED

0 of 30 paid calls toward a letter

Price

$0.01 per call

Paid calls

none yet

delivery unknown until someone pays

More info

Seller?

0xece637d7…1501ae8b

URL

https://api.x402ai.dev/api/embed

Seen

first 4 days ago · last 17 hr ago

7 free handshakes

Payment

Pays through

x402

Offered on?

Base USDC

Listed on?

Base

Handshakescomputed 7 hr ago

0.274 from 7 free handshakes over 30 days · UNRATED ?

How the composite of 0.274 is made up, part by part
Component	Weight	Measured	Lower bound ?		Adds	Short ?	Uncertain ?
livenesscosts the most it answered at all	0.60	1.00	0.123		0.074	0	−0.526
latency p95 it answered as fast as its class	0.20	0.00	0.000		0.000	−0.200	0
price stability the price stayed where it was listed	0.20	1.00	1.000		0.200	0	0
Composite	1.00		0.274	gap to 1.000 = 0.726 · 0.200 short · 0.526 uncertain	0.274	−0.200	−0.526

Not measured: correctness · nobody paid; honesty · nobody paid; schema conformance · no answer had a published shape to check

BURN_INFREE_TIER_ONLY

Verify it yourselfnpx teppi-check https://api.x402ai.dev/api/embedcurl -s https://api.teppi.xyz/v1/trust/cap_01M3RDKKYYEM9F1ZKVZYJER3S2