Model Library/Llama 4 Maverick Instruct
Llama 4 Maverick Instruct

Llama 4 Maverick Instruct

meta-llama/llama-4-maverick-17b-128e-instruct-fp8
by Meta
Input price
$0.27/ M tokens
Output price
$0.85/ M tokens
Context window
1Mtokens
Max output
8Ktokens

Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward pass (400B total). It supports multilingual text and image input, and produces multilingual text and code output across 12 supported languages. Optimized for vision-language tasks, Maverick is instruction-tuned for assistant-like behavior, image reasoning, and general-purpose multimodal interaction. Maverick features early fusion for native multimodality and a 1 million token context window. It was trained on a curated mixture of public, licensed, and Meta-platform data, covering ~22 trillion tokens, with a knowledge cutoff in August 2024. Released on April 5, 2025 under the Llama 4 Community License, Maverick is suited for research and commercial applications requiring advanced multimodal understanding and high model throughput.

Funktionen

Serverless API

Dokumentation

meta-llama/llama-4-maverick-17b-128e-instruct-fp8 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.

Verfügbare Serverless

Abfragen sofort ausführen, nur für die Nutzung bezahlen

Eingabe$0.27 / M Tokens
Ausgabe$0.85 / M Tokens

  1. API-Schlüssel erhalten

    Registrieren Sie sich und erstellen Sie einen Schlüssel, um den Code unten auszuführen. Die API ist OpenAI-kompatibel.

    AnmeldenAPI-Schlüssel erhalten

  2. 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-maverick-17b-128e-instruct-fp8
    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-maverick-17b-128e-instruct-fp8",
10    messages=[
11        {"role": "system", "content": "You are a helpful assistant."},
12        {"role": "user", "content": "Hello, how are you?"}
13    ],
14    max_tokens=8192,
15    temperature=0.7
16)
17
18print(response.choices[0].message.content)