Llama 4 Maverick is a natively multimodal mixture-of-experts model with 17 billion active parameters across 128 experts and 400 billion total parameters. Released in April 2025, it features a 1-million-token context window, letting it handle long documents and reasoning tasks that combine text with visual content. The model uses an early-fusion architecture to integrate text and image tokens natively, supporting multi-image inputs alongside text prompts. It was trained on roughly 22 trillion tokens of multimodal data with an August 2024 knowledge cutoff, and Meta positions it for visual recognition, image reasoning, captioning, and visual question answering. It is offered in both BF16 and FP8 formats and runs on a single H100 host or distributed setups. Meta reports that Maverick beats GPT-4o and Gemini 2.0 Flash across a broad range of widely reported benchmarks, making it well suited to applications that need strong image understanding and reasoning over visual information at scale.
Llama 4 Maverick 17B 128E Instruct FP8 runs on 2 different routes through the Opper gateway. Compare residency, ZDR, and training posture at a glance — full data-handling detail per route below.
Training posture across routes: No training on prompts by default.
Each route hosting Llama 4 Maverick 17B 128E Instruct FP8 has its own privacy posture, residency, and GDPR terms. Postures are maintained by Opper with a last-verification timestamp.
Zero data retention is available via Opper Enterprise contract. No training on customer data. US; unknown.
Zero data retention is available via Opper Enterprise contract. No training on customer data. US; SCCs; DPA available.
Call Llama 4 Maverick 17B 128E Instruct FP8 through the Opper gateway with one API key. Let your coding agent set it up, or call it directly — Opper is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.
Copy this and paste it into your coding agent — Claude Code, Cursor, Codex, and more — and it'll wire up Opper for you.
import OpenAI from "openai";const client = new OpenAI({apiKey: process.env.OPPER_API_KEY,baseURL: "https://api.opper.click/v3/compat",});const completion = await client.chat.completions.create({model: "deepinfra/meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",messages: [{ role: "user", content: "Hello" }],});console.log(completion.choices[0].message.content);
Side-by-side on privacy, EU hosting, pricing, and benchmarks.
