Llama 4 Scout

Meta chattool_usevision 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 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 (text and image) and multilingual output (text and code) across 12 supported languages. Designed for assistant-style interaction and visual reasoning, Scout uses 16 experts per forward pass and features a context length of 10 million tokens, with a training corpus of ~40 trillion tokens. Built for high efficiency and local or commercial deployment, Llama 4 Scout incorporates early fusion for seamless modality integration. It is instruction-tuned for use in multilingual chat, captioning, and image understanding tasks. Released under the Llama 4 Community License, it was last trained on data up to August 2024 and launched publicly on April 5, 2025.

๐Ÿ’ฐ
Price Ranking
#692 lowest price among 1240 Chat models

Model Specifications

Context Length
1.3M
Max Output
8k
Release Date
2025-04-05
Capabilities
chat tool_use vision
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 1.3M chat tool_use vision
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
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)