Llama 4 Scout 17B 16E Instruct (Free)
Chat CompletionsLlama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model from 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, it is instruction-tuned for multilingual chat, captioning, and image understanding.
Pricing
Pay-as-you-go rates for this model. More details can be found here.
Free
Capabilities
Input Modalities
Output Modalities
Supported Parameters
Available parameters for API requests
Usage Analytics
Token usage of this model on our platform
Throughput
Time-To-First-Token (TTFT)
Not enough TTFT data
Code Example
Example code for using this model through our API with Python (OpenAI SDK) or cURL. Replace placeholders with your API key and model ID.
Basic request example. Ensure API key permissions. For more details, see our documentation.
from openai import OpenAI
client = OpenAI(
base_url="https://api.naga.ac/v1",
api_key="YOUR_API_KEY",
)
resp = client.chat.completions.create(
model="llama-4-scout-17b-16e-instruct:free",
messages=[
{{"role": "user", "content": "What's 2+2?"}}
],
temperature=0.2,
)
print(resp.choices[0].message.content)