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Llama-4-Maverick-17B-128E-Instruct-FP8

Get API key
meta/llama-4-maverick-17b-128e-instruct-fp8
Input → Output
Text, Image Text
Access
Token Exchange
Context window
1,048,576 tokens
License: open_weights

From model to application

Quick Start

API reference

  1. Get your API key

    Create a key in the ShareAI Console, then save it as an environment variable on your server.

    Create API key
    Environment variable
    export SHAREAI_API_KEY="your-api-key"

  2. Choose your endpoint

    Send a POST request with your API key in the Authorization header.

    POSThttps://api.shareai.now/api/v1/chat/completions

  3. Make your first request

    The request below uses your selected tag. Run it on your server to keep your API key private.

    cURL
    curl --request POST 'https://api.shareai.now/api/v1/chat/completions' \
  --header "Authorization: Bearer ${SHAREAI_API_KEY}" \
  --header 'Content-Type: application/json' \
  --data-raw '{
  "model": "meta/llama-4-maverick-17b-128e-instruct-fp8",
  "messages": [
    {
      "role": "user",
      "content": "Hello!"
    }
  ],
  "stream": false
}'
    Python
    import json
import os
import urllib.request

payload = json.loads("{\n  \"model\": \"meta/llama-4-maverick-17b-128e-instruct-fp8\",\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"Hello!\"\n    }\n  ],\n  \"stream\": false\n}")
request = urllib.request.Request("https://api.shareai.now/api/v1/chat/completions",
    data=json.dumps(payload).encode(),
    headers={
        "Authorization": f"Bearer {os.environ['SHAREAI_API_KEY']}",
        "Content-Type": "application/json",
    },
    method="POST",
)
with urllib.request.urlopen(request) as response:
    print(json.load(response))
    TypeScript
    const response = await fetch("https://api.shareai.now/api/v1/chat/completions", {
  method: 'POST',
  headers: {
    Authorization: `Bearer ${process.env.SHAREAI_API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    "model": "meta/llama-4-maverick-17b-128e-instruct-fp8",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ],
    "stream": false
  }),
});
if (!response.ok) throw new Error(await response.text());
console.log(await response.json());

Token Exchange

Available through Token Exchange

Use the network with your token balance. Your account’s consumption settings determine how requests are billed.

A little more detail

Frequently asked questions

What is Llama-4-Maverick-17B-128E-Instruct-FP8?

Llama-4-Maverick-17B-128E-Instruct-FP8 is a model by Meta listed in the ShareAI catalog. Select a tag to see its specifications.

How much does Llama-4-Maverick-17B-128E-Instruct-FP8 cost?

This tag is available through Token Exchange. Your token balance and account consumption settings determine access and billing. Check your Console for your balance and eligibility.

What inputs and outputs does Llama-4-Maverick-17B-128E-Instruct-FP8 support?

Inputs: Text, Image. Outputs: Text. These capabilities apply to the selected model tag. Check the endpoint documentation for supported request formats.

What is the context length of Llama-4-Maverick-17B-128E-Instruct-FP8?

This tag has a context window of 1,048,576 tokens. Context size and pricing thresholds are separate. Request limits can be lower for a particular deployment.

How do I use Llama-4-Maverick-17B-128E-Instruct-FP8 with ShareAI?

Create an API key in the ShareAI Console, choose a model tag, and send an authenticated request to the endpoint in Quick Start. Your key must have access to the chosen model. Keep your key on your server.