embed-large

Generate a text embedding vector using OpenAI text-embedding-3-large (3072 dimensions).

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.

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?

0x77065d81…16744121

URL

https://agent402.tools/api/embed-large

MCP server on this host: io.github.MikeyPetrillo/agent402

Seen

first 35 days ago · last 21 hr ago

64 free handshakes

Payment

Pays through

x402 · MPP evm, tempo

Offered on?

algorand:wGHE2Pwdvd7S12BL5FaOP20EGYesN73ktiC1qzkkit8=, eip155:10, eip155:1329, Polygon, eip155:143, Arbitrum, eip155:42220, Avalanche, Robinhood Chain, Base USDC, Solana, stellar:pubnet, Tempo USDC.e

Listed on?

Polygon, Arbitrum, Avalanche, Base, Solana

Handshakescomputed 1 day ago

0.718 from 56 free handshakes over 30 days · UNRATED ?

How the composite of 0.718 is made up, part by part
Component	Weight	Measured	Lower bound ?		Adds	Short ?	Uncertain ?
latency p95costs the most it answered as fast as its class	0.20	0.00	0.000		0.000	−0.200	0
liveness it answered at all	0.60	0.99	0.864		0.518	−0.008	−0.073
price stability the price stayed where it was listed	0.20	1.00	1.000		0.200	0	0
Composite	1.00		0.718	gap to 1.000 = 0.282 · 0.208 short · 0.073 uncertain	0.718	−0.208	−0.073

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://agent402.tools/api/embed-largecurl -s https://api.teppi.xyz/v1/trust/cap_01M1A5A1DMWEQ2248J1ZHEP91E