Llama 4 Scout

Meta chatvisiontool_use Long

API ID: meta-llama/llama-4-scout-17b-16e-instruct

Input Price
$0.08
/1M tokens
Output Price
$0.30
/1M tokens

About Llama 4 Scout

Llama 4 Scout is Meta's efficient model from the Llama 4 generation, designed for practical deployment while delivering strong capability. The model features improved architecture and training that enables better performance per parameter than previous generations. Llama 4 Scout excels at general reasoning, coding, and multilingual tasks while maintaining efficient inference. It supports an extended context window and function calling for building AI agents. The open weights enable self-hosting, fine-tuning, and customization without API dependencies. For developers seeking capable open-source AI with the latest Meta improvements, Llama 4 Scout offers excellent value. It's particularly valuable for applications requiring strong capability with practical resource requirements.

๐Ÿ’ฐ
Price Ranking
#650 lowest price among 950 Chat models

Model Specifications

Context Length
328k
Max Output
16k
Release Date
2025-04-05
Capabilities
chat vision tool_use
Input Modalities
textimage
Output Modalities
text

Best For

  • Image analysis, document understanding, visual Q&A
  • Conversations, content writing, general assistance

๐Ÿ’ฐ Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$0.13
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$3.90
/month
1000 tickets/day, ~800 tokens each

Meta Model Lineup

Compare all models from Meta to find the best fit

Model Input Output Context Capabilities
Llama 4 Scout Current Free Free 328k chat vision tool_use
Llama 3.2 3B Instruct Free Free 80k chat tool_use
Llama 3 70B (Base) Free Free 8k chat
Llama 3 70B (Base) Free Free 8k chat
LlamaGuard 2 8B Free Free 8k chat
Llama 3 8B (Base) Free Free 8k chat

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๐Ÿš€ Quick Start

Get started with Llama 4 Scout API

OpenAI-compatible SDK
from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="meta-llama/llama-4-scout-17b-16e-instruct",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)