BAAI: bge-m3
baai/bge-m3The 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.
- Context window
- 8,194 tokens
- Input
- text
- Output
- embeddings
- Relay support
- Price book only
Reference prices & points
Our global markup: 15% · 1 USD = 10,000 points · Price version 0
| Billing unit | OpenRouter / USD | Our reference / USD | Points |
|---|---|---|---|
| Input / 1M tokens | $0.01 | $0.0115 | 115 |
| Output / 1M tokens | $0 | $0 | 0 |
Actual charge = the OpenRouter request cost × the markup locked for that request. Catalogue rates may be routing references; caching, long context, images and audio are charged when used. Listed prices do not mean every capability is available through this relay.
Catalogue time: 2026-11-11T23:25:37.465Z · Live catalogue
View all upstream price fields
{
"prompt": "0.00000001",
"completion": "0"
}Integration & availability
This model is listed in the price book but cannot be called from this workspace. The workspace supports text chat, vision and optional web search. Turn on Image mode to find eligible image generators. Other modalities are currently price-book entries.