DEMO LABS · DEMO RESOURCE

VECTOR EMBED 4

Embedding model for semantic search, retrieval and knowledge indexing across applications.

Use in terminal Open playground

Capabilities

EmbeddingsSemantic searchRetrieval

Modalities

textembeddings

Performance characteristics

Retrieval quality: High
Latency profile: Instant
Best for: Search and RAG
Context: 8K input

Privacy characteristics

This resource supports transient processing — requests can be processed without being treated as permanent user history, where the underlying infrastructure allows it.

Compute pricing (demo)

Input: 0.1 credits
Output: —
Unit: per 1M units (demo)

API identifier

demo/vector-embed-4

Example request

curl https://api.intellex.ai/v1/generate \
  -H "Authorization: Bearer $INTELLEX_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "demo/vector-embed-4",
    "input": "Your request here"
  }'

Illustrative shape only — the Intellex API is not live in this demo.

Demo interface — no live execution behind this panel