Is Qwen 3.8 Max available with Zero Data Retention on Elosia?

Qwen 3.8 Max runs on Elosia's standard backend; ZDR is available on many other models in the catalog.

How much does Qwen 3.8 Max cost on Elosia?

Qwen 3.8 Max is billed by usage at $2 per 1M input tokens and $6 per 1M output tokens, within your Elosia plan.

What is Qwen 3.8 Max's context window?

Qwen 3.8 Max supports a context window of up to 1,000,000 tokens.

Is Qwen 3.8 Max hosted in the EU?

Yes, Qwen 3.8 Max is available on Elosia's EU-hosted (EdenAI) backend for enterprise organizations.

When should you choose Qwen 3.8 Max?

Qwen 3.8 Max is a flagship model, best for the most demanding reasoning, agentic and long-context tasks.

Qwen 3.8 Max

QwenFlagship

ThinkingTool UseVisionStructured Output

About this model

Qwen3.8 Max is the flagship model in Alibaba's Qwen3.8 series, the general-availability successor to the Qwen3.8 Max Preview. It is a multimodal reasoning model intended for complex reasoning, visual understanding,...

Performance Tier

Flagship

Qwen 3.8 Max is a flagship model from Qwen : the most capable in their lineup.

Best-in-class model from this provider. Highest performance across benchmarks, ideal for demanding tasks.

Pricing

This model is included in Elosia plans

Moderate

Moderate cost. A balanced choice for regular use without constant cap watching.

Type	per 1M tokens
Input (prompt)	$2.00
Output (completion)	$6.00
Cache read	$0.250
Cache write	$2.50

Capabilities

Context Length1.0M

Max Output Tokens131K

TokenizerQwen

Inputtext, image, video

Outputtext

Release DateAugust 3, 2026

Benchmarks

General Intelligence

MMLU

Not reported

GPQA Diamond

92.6%

Mathematics

MATH-500

Not reported

Programming

HumanEval

Not reported

SWE-bench Verified

Not reported

Reasoning

IFEval

Not reported

Humanity's Last Exam

43.6%

Multimodal

MMMU-Pro

82.3%

Agentic

SWE-bench Pro

67.7%

Terminal-Bench 2.1

86.6%

Where does Qwen 3.8 Max stand?

Compare its performance index against every other model.

View the performance leaderboard

Recommended Use Cases

CodingAnalysisResearchGeneral ChatData Extraction

Strengths

Agentic behaviour carried by a 2.4T-parameter mixture of experts, only a fraction of which is engaged on each token
Tool calling with structured outputs, and up to 128K of output in a single response
Native video input alongside text and images, combined with a 1M-token context window
Vision goes past captioning: object detection and counting are part of the reported evaluation, on top of image and video inputs

Limitations

Weak factual reliability: on a question whose answer it does not know, it tends to produce a confident answer rather than abstain
Software engineering on real repositories trails its reasoning results, and the weights are closed, with no checkpoint published for self-hosting or auditing