thenlper

Thenlper: GTE-Base

thenlper/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.

embeddings

Catalog only: this interface is not available on Jevrouter or has no active image provider.

Provider-supported parameters

These are upstream capabilities. Jevrouter supports the subset described in the API contract; chat input is currently text only.

Capabilities are imported from OpenRouter’s catalog. This does not mean every model has been independently tested by Jevrouter.

Catalog updated: 2026-11-11T20:54:46.466Z · Price version: cmvv9vcm71o8rid10r19yw9ip:2

Provider pricing fields · USD per indicated unit

{
  "prompt": "0.000000005",
  "completion": "0"
}

Plan your integration

Connect with the OpenAI Python SDK →Estimate this model’s cost →Budgets, request status and safe retries →

Source: OpenRouter model catalog. Imported descriptions and capabilities are provider declarations, not independent benchmark results. Jevrouter currently uses OpenRouter as its managed upstream.