Bge Base En V1.5
The bge-base-en-v1.5 embedding model converts English sentences and paragraphs into 768-dimensional dense vectors, delivering efficient, high-quality semantic embeddings optimized for retrieval, semantic search, and document-matching workflows. This version (v1.5) features...
Cheapest input
$0.005
$/MTok · OpenRouter
Cheapest output
$0
$/MTok
Context
512
tokens
Sources
2
4 listings
Sources
Same model, different sources. Our first-party rate is listed first, then router and aggregator rows stay separate so you can see the spread instead of a single blended number.
| Source | Provider | Input | Output | Cache read | Context |
|---|---|---|---|---|---|
| OpenRoutercheapestbaai/bge-base-en-v1.5 | OpenRouter | $0.005 | $0 | $0 | 512 |
| LiteLLMtogether_ai/BAAI/bge-base-en-v1.5 | N/A | $0.008 | $0 | $0.0008 | N/A |
| LiteLLMBAAI/bge-base-en-v1.5 | N/A | $0.008 | $0 | $0.0008 | N/A |
| LiteLLMbge-base-en-v1.5 | N/A | $0.008 | $0 | $0.0008 | N/A |
Capabilities
- In: text
- Out: embeddings
Run this model in a real workspace
Launch agents from the project they work in, use remote management to reach another machine, and see this model's sessions and token usage in your own history. Free to use, runs on your device.
Data and list-price estimates may contain mistakes. Not investment advice.