Llama 4 Scout 17B 16E Instruct

by Meta

Llama 4 Scout is a natively multimodal mixture-of-experts model with 17 billion active parameters across 16 experts and 109 billion total parameters. Released in April 2025, it is built for efficiency, fitting on a single NVIDIA H100 GPU with Int4 quantization while holding strong performance across reasoning, coding, and visual understanding. As served here it supports a 128,000-token context window. Scout was trained on roughly 40 trillion tokens of data covering 200 languages, with dedicated fine-tuning support for 12 languages, and has an August 2024 knowledge cutoff. It uses early fusion for native multimodality and includes architecture features such as NoPE layers and chunked attention to help with long-context handling. The model supports tool use and structured output, which makes it flexible for agentic workflows. Compared to its larger Maverick sibling, Scout prioritizes efficiency and deployability while keeping strong image grounding and visual question-answering capability. Meta reports it outperforms Gemma 3, Gemini 2.0 Flash-Lite, and Mistral 3.1 across a broad range of widely reported benchmarks.

Key info

Input
Output
Features
Context window
328K
Max output
328K
Input price
$0.08 /1M
Output price
$0.30 /1M
  • US residency available
  • Zero data retention via Enterprise
  • No training by default
  • GDPR DPA available

Available routes

Llama 4 Scout 17B 16E Instruct runs on 3 different routes through the Opper gateway. Compare residency, ZDR, and training posture at a glance β€” full data-handling detail per route below.

ProviderRegionZero data retentionTrainingInputOutput
DeepInfraUSEnterpriseNo$0.08$0.30
GroqUSEnterpriseNo$0.11$0.34
NovitaUSEnterpriseNo$0.18$0.59

Training posture across routes: No training on prompts by default.

Data handling per route

Each route hosting Llama 4 Scout 17B 16E Instruct has its own privacy posture, residency, and GDPR terms. Postures are maintained by Opper with a last-verification timestamp.

DeepInfra β€” United StatesπŸ‡ΊπŸ‡Έ

Zero data retention is available via Opper Enterprise contract. No training on customer data. US; unknown.

Zero data retention
Available via Opper Enterprise contract.
Training
No training on customer data.
Logging
Limited debug logs
Third-party access
None disclosed
GDPR DPA
No DPA
Transfer mechanism
unknown

Groq β€” United StatesπŸ‡ΊπŸ‡Έ

Zero data retention is available via Opper Enterprise contract. No training on customer data. US; SCCs; DPA available.

Zero data retention
Available via Opper Enterprise contract.
Training
No training on customer data.
Logging
Abuse monitoring (30-day retention)
Third-party access
Provider may share with subprocessors / partners
GDPR DPA
DPA available
Transfer mechanism
SCCs

Novita β€” United StatesπŸ‡ΊπŸ‡Έ

Zero data retention is available via Opper Enterprise contract. No training on customer data. US; SCCs; DPA available.

Zero data retention
Available via Opper Enterprise contract.
Training
No training on customer data.
Logging
Abuse monitoring
Third-party access
None disclosed
GDPR DPA
DPA available
Transfer mechanism
SCCs

Get started

Call Llama 4 Scout 17B 16E Instruct through the Opper gateway with one API key. Let your coding agent set it up, or call it directly β€” Opper is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.

Set it up with your agent

Copy this and paste it into your coding agent β€” Claude Code, Cursor, Codex, and more β€” and it'll wire up Opper for you.

Or call it directly

import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.OPPER_API_KEY,
baseURL: "https://api.opper.ai/v3/compat",
});
const completion = await client.chat.completions.create({
model: "deepinfra/meta-llama/Llama-4-Scout-17B-16E-Instruct",
messages: [{ role: "user", content: "Hello" }],
});
console.log(completion.choices[0].message.content);

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Llama 4 Scout 17B 16E Instruct by Meta β€” pricing, benchmarks | Opper AI