Model card

Qwen3-Embedding 8B

lx1-qwen3-embed-8bEmbeddingsLive in the catalog

The largest Qwen3 embedding: strong multilingual retrieval with 4,096-dimensional vectors and instruction-awareness, so you can steer the embedding toward a task. A capable choice when you want maximum retrieval quality.

Max input32K tokens

Input · per Mtok$0.05

Dimensions4,096

Served byLayer X1 engine

Where it earns its keep[01/03]

01High-dimensional multilingual vectors
02Instruction-aware embeddings
03Strong on cross-lingual retrieval

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.

Qwen3-Embedding 8B 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-qwen3-embed-8b",
    "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.

Your agent doesn't change.
Everything underneath does.

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

Get a key Read the docs

Start free · no card · Starter from $5/mo

One endpoint. Served by our engine.

Your agent doesn't change.Everything underneath does.

Your agent doesn't change.
Everything underneath does.