Using Gemini Embedding on Vercel AI Gateway

Implementation guide · Gemini Embedding · Google DeepMind

Serverless

Vercel AI Gateway exposes Gemini Embedding through model ID google/gemini-embedding-001. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-06-29. Next refresh: weekly.

Quick Start

1
Create an account at Vercel AI Gateway and generate an API key.
2
Use the Vercel AI Gateway SDK or REST API to call google/gemini-embedding-001 — see the documentation for request format.
3
You'll be billed $0.15/1M input. See full pricing.

API Portal Documentation Pricing Model Card

Code Examples

Install

pip install openai

API key

AI_GATEWAY_API_KEY

Model ID

google/gemini-embedding-001

creator/model-name e.g. kwaipilot/kat-coder-pro-v2

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AI_GATEWAY_API_KEY"],
    base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
    model="google/gemini-embedding-001",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Pricing on Vercel AI Gateway

Type	Price (per 1M)
Input tokens	$0.15

Capabilities

No model capability flags are currently sourced.

About Gemini Embedding

Gemini Embedding is a language model from Google DeepMind focused on text embeddings for retrieval and semantic search. It was released 2023-12-13.

Full model details →

Model Specs

Released2023-12-13

Vercel