Using text-embedding-3-large on Vercel AI Gateway

Implementation guide · text-embedding-3 · OpenAI

Serverless

Vercel AI Gateway exposes text-embedding-3-large through model ID openai/text-embedding-3-large. 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 openai/text-embedding-3-large — see the documentation for request format.
3
You'll be billed $0.13/1M input. See full pricing.

API Portal Documentation Pricing Model Card

Code Examples

Install

pip install openai

API key

AI_GATEWAY_API_KEY

Model ID

openai/text-embedding-3-large

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="openai/text-embedding-3-large",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Pricing on Vercel AI Gateway

Type	Price (per 1M)
Input tokens	$0.13

Capabilities

No model capability flags are currently sourced.

About text-embedding-3-large

OpenAI's most capable text embedding model with 3072 output dimensions (configurable). Supports Matryoshka representation learning for smaller embeddings with reduced quality loss.

Full model details →

Model Specs

Released2024-01-25

Context8k

Knowledge cutoff2021-09

Vercel