Skip to main content
Orux AIOruxAI
Google logo

Google

gemini-embedding-2-preview

gemini-embedding-2-preview

Generate content through the unified API.

Pricing
From 12.71 Credits / 1M text units(≈ $0.0635)
Output
Embeddings
Added to catalog
Nov 1, 2026
Input
Examples
*
Item 1
Item 2

Estimate the cost first. Generation starts only after confirmation.

OutputFill example
{ "object": "list", "note": "Embedding excerpt: first 8 dimensions per vector.", "data": [ { "index": 0, "dimensions": 3072, "embeddingExcerpt": [ -0.0008123586, 0.0052316114, -0.0033130453, -0.02267119, -0.007943681, 0.012904237, -0.0048037595, 0.019806819 ] }, { "index": 1, "dimensions": 3072, "embeddingExcerpt": [ -0.0049683694, 0.0014597271, -0.010747084, -0.015489507, -0.037212707, 0.025356414, 0.008165206, 0.0036767288 ] } ] }

README

Generate content through the unified API.

Model capabilities

Input modalities
Text

Parameters

Fields accepted in the request body for this model.

inputobject
Required

Pricing

Credits / 1M text units
Input
12.71 Credits≈ $0.0635
Official reference $0.2068% below official

Bill actual quantity · Rounding is applied once to the total cost

Official pricing source · Verified 2026-11-01

Prices are billed per unit consumed with no monthly minimum. See billing guide for Credits estimates and actual usage charges.

POST https://orux.top/api/v1/embeddings

Frequently asked questions

About gemini-embedding-2-preview pricing, capabilities and API access on Orux AI.

What is gemini-embedding-2-preview?

gemini-embedding-2-preview: Generate content through the unified API.

How much does gemini-embedding-2-preview cost on Orux AI?

Input: 12.70608 Credits; output: 0 Credits, per 1M text units. See the pricing section on this page for gemini-embedding-2-preview pricing and applicable conditions. Charges depend on the selected parameters and recorded usage.

Where can I access the gemini-embedding-2-preview API?

Create an Orux AI API key and send an authenticated POST request to https://orux.top/api/v1/embeddings, using gemini-embedding-2-preview as the model identifier. Try the playground on this page and use the API example for the exact request format.