Does Qwen3 Coder Next support zero data retention?

Yes. Qwen3 Coder Next is available with zero data retention by default on Geodd, Novita through the Opper gateway.

Where is Qwen3 Coder Next hosted?

Qwen3 Coder Next runs on US hosting routes through the Opper gateway.

Is Qwen3 Coder Next trained on prompts and outputs?

No. Every hosting route for Qwen3 Coder Next is configured so customer prompts and outputs are not used to train models by default.

Is a GDPR DPA available for Qwen3 Coder Next?

Yes. A GDPR Data Processing Agreement is available on at least one route serving Qwen3 Coder Next. Contact hello@opper.ai to receive it.

Qwen3 Coder Next

by Alibaba

Qwen3 Coder Next is an open-weight ultra-sparse Mixture-of-Experts model with 80 billion total parameters, activating just 3 billion per forward pass. It delivers roughly 10x higher throughput than comparable dense models, with a 256K context window extendable further for repository tasks. Released in February 2026 under the Apache 2.0 license, it scores 70.6 on SWE-Bench Verified and reports leading secure-code-generation results, outperforming a top proprietary model on the SecCodeBench security benchmark. It supports 370 programming languages with tool use and structured output for agentic coding. Open availability makes it practical to run frontier-grade local coding agents on-device, without cloud API dependency.

Open in playground Try in chat Compare

Key info

Input

Output

Features

Context window

262K

Max output

—

Input price

$0.08 /1M

Output price

$0.98 /1M

US residency available
Zero data retention on pay-as-you-go
No training by default
GDPR DPA available

Available routes

Qwen3 Coder Next 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.

Provider	Region	Zero data retention	Training	Input	Output
Geodd	US	Zero data retention	No	$0.08	$0.98
Novita	US	Enterprise	No	$0.20	$1.50

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

Data handling per route

Each route hosting Qwen3 Coder Next has its own privacy posture, residency, and GDPR terms. Postures are maintained by Opper with a last-verification timestamp.

Geodd — United States🇺🇸

Zero data retention is on by default on Pay-as-you-go — no action required. No training on customer data. US; SCCs.

Zero data retention: On by default on Pay-as-you-go.
Training: No training on customer data.
Logging: None
Third-party access: Provider may share with subprocessors / partners
GDPR DPA: No DPA
Transfer mechanism: SCCs

Novita — United States🇺🇸

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

Benchmarks

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

Global rank#178 of 531 LLMs

TierEfficient

Output speed81 tok/s

First token1.40s

Intelligence Index21.2

Coding Index22.9

Reasoning & knowledge

GPQA Diamond

74%

Humanity's Last Exam

Long-context reasoning

40%

Coding

SciCode

32%

Agentic & tool use

Terminal-Bench Hard

18%

τ²-Bench Telecom

80%

Math & instruction following

IFBench

35%

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

Get started

Call Qwen3 Coder Next 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 your coding agent — Claude Code, Cursor, Codex, and more — 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: "geodd:us/qwen3-coder-next",
10  messages: [{ role: "user", content: "Hello" }],
11});
12console.log(completion.choices[0].message.content);