Thenlper: GTE-Base

thenlper/gte-base

Released Nov 18, 2025512 context

$0.005/M input tokens$0/M output tokens

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.

Thenlper: GTE-Base

thenlper/gte-base

Released Nov 18, 2025512 context

$0.005/M input tokens$0/M output tokens

Providers for GTE-Base

OpenRouter routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

Performance for GTE-Base

Compare different providers across OpenRouter

Effective Pricing for GTE-Base

Actual cost per million tokens across providers over the past hour

Apps using GTE-Base

Top public apps this month

Recent activity on GTE-Base

Total usage per day on OpenRouter

Prompt

15M

Completion

Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length.

Uptime stats for GTE-Base

Uptime stats for GTE-Base across all providers

Sample code and API for GTE-Base

OpenRouter normalizes requests and responses across providers for you.

OpenRouter provides an OpenAI-compatible embeddings API that you can call directly, or using the OpenAI SDK.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.

GTE-Base - API Pricing & Providers | OpenRouter