gemini-embedding-001 provides a unified cutting edge experience across domains, including science, legal, finance, and coding. This embedding model has consistently held a top spot on the Massive Text Embedding Benchmark (MTEB) Multilingual leaderboard since the experimental launch in March.
Modalities
Price
$0.15per 1M tokens
Context
20K
Weekly Tokens
33B
Released
Oct 31, 2025
Create an API key from your OpenRouter dashboard and set it as an environment variable:
Use google/gemini-embedding-001 with the OpenRouter API:
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.
For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.
https://openrouter.ai/api/v1/embeddingsBearer $OPENROUTER_API_KEYapplication/jsonoptional — your site URL, for rankingsoptional — your site name, for rankingsgoogle/gemini-embedding-001| Name | Type | Default | Description |
|---|---|---|---|
max_tokens | integer | — | This sets the upper limit for the number of tokens the model can generate in response. |
temperature | float | 1 | This setting influences the variety in the model's responses. |
top_p | float | 1 | This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P. |
seed | integer | — | If specified, the inferencing will sample deterministically, such that repeated requests with the same seed and parameters should return the same result. |
response_format | map | — | Forces the model to produce specific output format. |