Does Llama 3.1 70B Instruct support zero data retention?

Not self-serve on Pay-as-you-go. Zero data retention for Llama 3.1 70B Instruct is available on request via Opper Enterprise — contact hello@opper.ai.

Where is Llama 3.1 70B Instruct hosted?

Llama 3.1 70B Instruct runs on US hosting routes through the Opper gateway.

Is Llama 3.1 70B Instruct trained on prompts and outputs?

No. Every hosting route for Llama 3.1 70B Instruct is configured so customer prompts and outputs are not used to train models by default.

Llama 3.1 70B Instruct

by Meta

Llama 3.1 70B Instruct is Meta's open-weight general-purpose model, released July 2024. With 70 billion parameters and a 131,072-token context window, it balances capability and efficiency, offering strong reasoning, instruction following, and multilingual fluency. The model handles tool calling, structured output generation, and complex reasoning workflows. It supports long-form generation, code understanding, and agentic behavior where tool use is central, and the extended context window supports document analysis and multi-turn conversations. As an open-weight model, it suits organizations that want customizable, auditable inference. Multilingual support officially spans eight languages, including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, making it practical for global applications.

Open in playground Try in chat Compare

Key info

Input

Output

Features

Context window

131K

Max output

131K

Input price

$0.40 /1M

Output price

$0.40 /1M

US residency available
Zero data retention via Enterprise
No training by default

Available routes

Llama 3.1 70B Instruct runs on 1 route through the Opper gateway. Compare residency, ZDR, and training posture at a glance — full data-handling detail per route below.

Provider	Region	Zero data retention	Training	Input	Output
DeepInfra	US	Enterprise	No	$0.40	$0.40

Uptime and availability

Llama 3.1 70B Instruct runs on a single route through the Opper gateway today, so its availability is that provider's availability.

99.34%route uptime, last 30 days

Single route, no failover target within this model.

Name a second model in the same request and the gateway tries it on retriable errors, so a busy hour never has to reach your users. Set up a fallback chain.

Measured over the last 30 days from each provider's official status feed via StatusGator. Refreshed hourly. See uptime for every provider Opper monitors.

Data handling per route

Each route hosting Llama 3.1 70B Instruct has its own privacy posture, residency, and GDPR terms. Postures are maintained by Opper with a last-verification timestamp.

DeepInfra — United States🇺🇸

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

Benchmarks

Independent benchmark scores — composite indices for reasoning, coding, and math, plus individual eval scores where available.

Global rank#458 of 583 LLMs

TierEfficient

Output speed0 tok/s

First token0.00s

Intelligence Index6.5

Math Index4.0

Reasoning & knowledge

MMLU-Pro

68%

GPQA Diamond

41%

Humanity's Last Exam

Long-context reasoning

Coding

LiveCodeBench

23%

SciCode

27%

Agentic & tool use

Terminal-Bench Hard

τ²-Bench Telecom

15%

Math & instruction following

AIME 2025

IFBench

34%

See full leaderboard →Benchmarks via Artificial Analysis · View on AA

Get started

Call Llama 3.1 70B Instruct 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.

Set it up with your agent

Copy this and paste it into a coding agent like Claude Code, Cursor or Codex and it'll wire up Opper for you.

Or call it directly

1import OpenAI from "openai";
2
3const client = new OpenAI({
4  apiKey: process.env.OPPER_API_KEY,
5  baseURL: "https://api.opper.ai/v3/compat",
6});
7
8const completion = await client.chat.completions.create({
9  model: "deepinfra/meta-llama/Meta-Llama-3.1-70B-Instruct",
10  messages: [{ role: "user", content: "Hello" }],
11});
12console.log(completion.choices[0].message.content);