BGE Large EN v1.5
sdn-bge-large-enEmbeddingsLive in the catalogThe highest-accuracy English option: 1024 dimensions give it room to separate passages that a smaller model collapses together. Reach for it when retrieval quality is the bottleneck in your pipeline and a wider index is an acceptable cost.
- 01Best English retrieval accuracy here
- 021024 dimensions for finer separation
- 03Strong on near-duplicate passages
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.
One endpoint. Served by our engine.
BGE Large 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.
curl https://api.sideren.io/v1/embeddings \
-H "authorization: Bearer sdn_your_key" \
-H "content-type: application/json" \
-d '{
"model": "sdn-bge-large-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.
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