Using Llama 4 Scout 17B-16E Instruct on Vercel AI Gateway

Implementation guide · Llama 4 · AI at Meta

ServerlessOpen Weights

Vercel AI Gateway exposes Llama 4 Scout 17B-16E Instruct through model ID meta/llama-4-scout. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-07-09. 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 meta/llama-4-scout — see the documentation for request format.
3
You'll be billed $0.17/1M input, $0.66/1M output tokens. See full pricing.

API Portal Documentation Pricing Model Card

Code Examples

Install

pip install openai

API key

AI_GATEWAY_API_KEY

Model ID

meta/llama-4-scout

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="meta/llama-4-scout",
    messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)

Pricing on Vercel AI Gateway

Type	Price (per 1M)
Input tokens	$0.17
Output tokens	$0.66

Capabilities

VisionMultimodalStructured Outputs

About Llama 4 Scout 17B-16E Instruct

Meta's Llama 4 Scout is a 17-billion parameter mixture-of-experts model with 16 expert routing. Optimized for efficient inference on edge and cloud environments with strong multi-turn conversation capabilities. Available on Cloudflare Workers AI.

Full model details →

Model Specs

Released2025-04-05

Parameters109B (17B active)

Context10m

ArchitectureMixture of Experts

Knowledge cutoff2024-08

Vercel