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text-embedding-3-small

lx1-embed-3-smallEmbeddingsLive in the catalog

The economical OpenAI embedding: markedly cheaper than the large model while keeping most of its retrieval quality. The right pick for high-volume indexing where you're embedding millions of chunks and cost dominates.

Max input8K tokens
Input · per Mtok$0.02
Dimensions1,536
Served byLayer X1 engine
Where it earns its keep[01/03]
  • 01Very low price per million tokens
  • 02Most of the large model's quality
  • 03Ideal for high-volume indexing
Capabilities
EmbeddingsYes

Turns text into a fixed-length vector for semantic search, RAG, clustering, and dedupe. Call it on /v1/embeddings with a string or array of inputs — no chat, tools, or reasoning.

Behind the endpoint[02/03]

One endpoint. Served by our engine.

text-embedding-3-small is served through the Layer X1 engine — zero-downtime serving is the design target, not a status-page apology. You request it by name; everything else is our problem.

Call it by name
curl https://api.layerx1.in/v1/embeddings \
  -H "authorization: Bearer lx1_your_key" \
  -H "content-type: application/json" \
  -d '{
    "model": "lx1-embed-3-small",
    "input": "text to embed"
  }'

OpenAI-style clients work too — POST the same model name to /v1/embeddings with a Bearer key. See the docs for both dialects.

Put your agent on real infrastructure

Your agent doesn't change.
Everything underneath does.

$export ANTHROPIC_BASE_URL=https://api.layerx1.in

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