GTE-Large
The gte-large embedding model converts English sentences, paragraphs and moderate-length documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for information retrieval, semantic textual similarity, reranking and...
Cheapest input
$0.01
$/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-large | OpenRouter | $0.01 | $0 | $0 | 512 |
| LiteLLMfireworks_ai/thenlper/gte-large | — | $0.016 | $0 | $0.0016 | — |
| LiteLLMthenlper/gte-large | — | $0.016 | $0 | $0.0016 | — |
| LiteLLMgte-large | — | $0.016 | $0 | $0.0016 | — |
Capabilities
- In: text
- Out: embeddings