GTE-Base
The gte-base embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, delivering efficient and effective semantic embeddings optimized for textual similarity, semantic search, and clustering applications.
Cheapest input
$0.005
$/MTok · OpenRouter
Cheapest output
$0
$/MTok
Context
512
tokens
Offers
4
2 sources
Offers
Same model, different listings. First-party, 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 |
|---|---|---|---|---|---|
| OpenRoutercheapestthenlper/gte-base | OpenRouter | $0.005 | $0 | $0 | 512 |
| LiteLLMfireworks_ai/thenlper/gte-base | — | $0.008 | $0 | $0.0008 | — |
| LiteLLMthenlper/gte-base | — | $0.008 | $0 | $0.0008 | — |
| LiteLLMgte-base | — | $0.008 | $0 | $0.0008 | — |
Capabilities
- In: text
- Out: embeddings