Can you shorten the embedding dimensions of Gemini Embedding model?

Gemini Embedding model supports dimension reduction. Check the API documentation for available dimension sizes.

How many inputs can you send to Gemini Embedding model per request?

Gemini Embedding model supports batch input. Check the API documentation for maximum inputs per request.

Does Gemini Embedding model have a batch discount?

Gemini Embedding model may offer batch pricing. Check your MixRoute console for current rates.

How do you start calling Gemini Embedding model?

Set the model parameter to “gemini-embedding-001” and use your MixRoute API key. Compatible with OpenAI SDK.

What is the rate limit for Gemini Embedding model?

Rate limits for Gemini Embedding model depend on your MixRoute plan tier. Check your console quota.

How much does it cost to embed a million records with Gemini Embedding model?

Gemini Embedding model is billed per input token at 0.15 USD per 1,000,000 tokens. One million records cost the listed rate multiplied by the total tokens those records produce; the default output dimension is 3,072.

Can you call Gemini Embedding model with the OpenAI SDK you already use?

Yes. Gemini Embedding model is reachable through an OpenAI-compatible endpoint, so an existing OpenAI SDK client works after pointing the base URL at MixRoute and setting the model parameter to gemini-embedding-001 . Keep your current request and response handling.

Model detail

Gemini Embedding model

Provided by Google

Pay-as-you-go

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.

Model specs

Model ID: gemini-embedding-001

Context length: 2.048K
Max output: –
I/O modalities
Released: 2025-10

API endpoints

One MixRoute gateway, OpenAI-compatible

Gemini /v1beta/models/{model}:generateContent POST
OpenAI-compatible /v1/chat/completions POST

Pricing

Flat rate, unit: /1M Tokens

Input

$0.1500 /1M Tokens

Completion

$0.6000 /1M Tokens

Selection summary

Quickly judge whether it fits your workload

What is this model good for?

Embeddings model for semantic search

Gemini Embedding — High-dimensional vector representation for text and images, efficient numerical mapping.

What should you check before using it?

2,048 context, N/A (embeddings) output

Embeddings. Knowledge cutoff: 2025-05. Released 2025-06.

Why use it through MixRoute?

Available through MixRoute's OpenAI-compatible endpoint

Use the Google Gen AI SDK or call through MixRoute. Set the model parameter to "gemini-embedding-001".

Capabilities & compatibility

Unconfirmed capabilities stay "Unknown," no guesses

OpenAI SDK

Call Gemini Embedding model through MixRoute's OpenAI-compatible endpoint.

EX Change base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.

Token cost estimator

Live estimate from this page's pricing, not an actual bill

Input tokens Max per request 2.048K

Output tokens

Requests / month

Cache hit rate –

This model has no cache-read price; caching is not counted

FAQ

Get started

01

Create an API key

Generate a key in the Console; one key calls every model.
02

Set the base URL

Fully OpenAI SDK-compatible; just swap the URL to connect.

https://api.mixroute.ai/v1
03

Specify the model ID

In the request's model field, enter:

gemini-embedding-001

Create an API key

New users get $5 in free credits

Test this model and alternate routes with the same request format

Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.

Create an API key View integration docs