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meta-llama/llama-4-scout

meta-llama/llama-4-scout

327,680 context · $0.18/M input tokens · $0.59/M output tokens

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

Pricing

Pay-per-use

No upfront costs, pay only for what you use

Input$0.18 / M Tokens
Output$0.59 / M Tokens

Try the model

meta-llama/llama-4-scout
Online
meta
Hi! I am a helpful AI assistant. What can I do for you?

API Usage

Use the following code examples to integrate with our API:

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="meta-llama/llama-4-scout",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

Model Introduction

Meta-Llama llama-4-scout

meta-llama llama-4-scout


Why It Looks Great

  • Large Language Model architecture for efficient processing
  • 327680 context window for long document handling
  • Competitive pricing at $0.1/$0.3 per million tokens

Key Features

  • Context Window: 327680 tokens
  • Max Output: 16384 tokens
  • Vision: Supported
  • Function Calling: Supported

Specifications

SpecificationValue
ProviderMeta-Llama
Model TypeLarge Language Model (LLM)
ArchitectureN/A
Context Window327680 tokens
Max Output16384 tokens
InputText
OutputText
VisionSupported
Function CallingSupported

Pricing

Token TypeCost per Million Tokens
Input$0.1
Output$0.3

How to Use

  1. Write your prompt — describe the task, provide context, and specify desired output format.
  2. Submit — the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: meta-llama/llama-4-scout


API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="meta-llama/llama-4-scout",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "meta-llama/llama-4-scout",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: meta-llama/llama-4-scout
  • Provider: Meta-Llama

Info

Providermeta
Typellm

Supported Functionality

Input
TextImage
Output
Text
Context327,680
Max Output16,384
Vision✓ Supported
Function Calling✓ Supported

API Access Guide

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
Model IDmeta-llama/llama-4-scout

Llama 4 Scout API

meta-llama/llama-4-scout

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

Input

$0.18 /M

Output

$0.59 /M

Context

328K

Max Output

16K

Vision

Supported

Tool Use

Supported

Try Llama 4 Scout on WaveSpeedAI

Access Llama 4 Scout through our unified API — OpenAI-compatible, no cold starts, transparent pricing.

Frequently Asked Questions about Llama 4 Scout

How much does Llama 4 Scout cost via the API?+

Pricing on WaveSpeedAI: $0.18 per million input tokens and $0.59 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.

What is the context window of Llama 4 Scout?+

Llama 4 Scout supports up to 328K tokens of context with up to 16K tokens of output per request.

Is Llama 4 Scout OpenAI-compatible?+

Yes. WaveSpeedAI exposes Llama 4 Scout through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.

How do I get started with Llama 4 Scout?+

Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate Llama 4 Scout before paying per token.

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