baai
BAAI: bge-m3
baai/bge-m3
The bge-m3 embedding model encodes sentences, paragraphs, and long documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for multilingual retrieval, semantic search, and large-context applications.
Catalog only: this interface is not available on Jevrouter or has no active image provider.
Provider-supported parameters
These are upstream capabilities. Jevrouter supports the subset described in the API contract; chat input is currently text only.
Capabilities are imported from OpenRouter’s catalog. This does not mean every model has been independently tested by Jevrouter.
Catalog updated: 2026-11-11T20:54:46.466Z · Price version: cmvv9vcp41o9lid106a9wsjxb:2
Provider pricing fields · USD per indicated unit
{
"prompt": "0.00000001",
"completion": "0"
}Plan your integration
Source: OpenRouter model catalog. Imported descriptions and capabilities are provider declarations, not independent benchmark results. Jevrouter currently uses OpenRouter as its managed upstream.