Model Library/Llama 4 Scout Instruct

Llama 4 Scout Instruct

meta-llama/llama-4-scout-17b-16e-instruct

by Meta

Input price: $0.18/ M tokens
Output price: $0.59/ M tokens
Context window: 128Ktokens
Max output: 128Ktokens

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.

Features

Serverless API

Docs

meta-llama/llama-4-scout-17b-16e-instruct is available via Novita's serverless API, where you pay per token. There are several ways to call the API, including OpenAI-compatible endpoints with exceptional reasoning performance.

Available Serverless

Run queries immediately, pay only for usage

Input$0.18 / M Tokens

Output$0.59 / M Tokens

Get your API key
Sign up and create a key to run the code below. The API is OpenAI-compatible.
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Make your first request

The API is OpenAI-compatible: point any OpenAI SDK at the base URL and pass this model ID.

Base URL: https://api.novita.ai/openai
Model ID: meta-llama/llama-4-scout-17b-16e-instruct
API Endpoint: chat/completionscompletions

1from openai import OpenAI
2
3client = OpenAI(
4    api_key="<Your API Key>",
5    base_url="https://api.novita.ai/openai"
6)
7
8response = client.chat.completions.create(
9    model="meta-llama/llama-4-scout-17b-16e-instruct",
10    messages=[
11        {"role": "system", "content": "You are a helpful assistant."},
12        {"role": "user", "content": "Hello, how are you?"}
13    ],
14    max_tokens=131072,
15    temperature=0.7
16)
17
18print(response.choices[0].message.content)