Model card

BGE Small EN v1.5

sdn-bge-small-enEmbeddingsLive in the catalog

The most compact embedding in the catalog. At 384 dimensions every vector costs half the storage of a 768-wide model and similarity search runs proportionally faster, which matters once an index reaches millions of chunks. The trade is a little accuracy on subtle distinctions.

Max input1K tokens

Input · per Mtok$0.03

Dimensions384

AvailabilityLive

Where it earns its keep[01/03]

01Half the index size of a 768-dim model
02Fastest similarity search here
03Cheapest per million tokens to embed

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.

BGE Small EN v1.5 is served through the Sideren 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.sideren.io/v1/embeddings \
  -H "authorization: Bearer sdn_your_key" \
  -H "content-type: application/json" \
  -d '{
    "model": "sdn-bge-small-en",
    "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.sideren.io

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.