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
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 |
|---|---|---|---|---|---|
| OpenRoutercheapestthenlper/gte-base | OpenRouter | $0.005 | $0 | $0 | 512 |
| LiteLLMfireworks_ai/thenlper/gte-base | N/A | $0.008 | $0 | $0.0008 | N/A |
| LiteLLMthenlper/gte-base | N/A | $0.008 | $0 | $0.0008 | N/A |
| LiteLLMgte-base | 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.