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Qwen: Qwen3.8 Max

58.0 / 100 1M context Proprietary

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,...

Editor's note

Written for AI Agent Hub. This is separate from the publisher description above.

What problem it solves

This row is a closed Qwen listing with a long claimed context and a high directory score. It solves "I want the hosted Max endpoint" for people allowed to call Alibaba's Qwen API. It does not solve "I want Qwen weights on my GPU."

Who it is for

API users comparing hosted flagships, who will pin this name rather than a dated sibling such as a 0902 snapshot unless they have a reason to pin the date. Read the company line. It should say the hosted Qwen publisher, not an open-weight mirror.

Who should skip it

Skip it when the data cannot leave your network. Search the open-source category for Qwen weights and read that license separately. The open versus proprietary guide warns that the brand is not the flag. Skip a batch variant if you are judging interactive latency. Batch is an endpoint mode.

First three steps

  1. Open Qwen's own model page and copy the id you will actually call.
  2. Compare price with one cheaper hosted model using your real prompt, not a slogan.
  3. Record whether the answer was acceptable and what it cost. Our score does not belong in that note.

Alternatives on this site

DeepSeek hosted rows and Claude Opus 5 are the other hosted conversations. Gemini Flash is the one to open if speed and price dominate. None of them inherit this row's contract.

Questions

Why are there several Qwen 3.8 rows? Dates, batch flags, and hosts differ. The row you configure is the row you pay for.

Is 2.4T parameters the activated size? Treat giant totals on mixture-style names as totals until the vendor says otherwise. Do not divide your GPU by that number. This row is hosted anyway. You will not load 2.4T, and you should not plan a machine as if you will.

Benchmark Scores

HLE
56.2
DeepSWE
56.6
GPQA-Diamond
92.6
Context-Arena
96.92
NL2Repo-Bench
55.9
SWE-Bench-Pro
67.7
AutomationBench
27.3
Agents-Last-Exam
27.0
Creative-Writing
1842.0
Terminal-Bench-2.1
86.6
Toolathlon-Verified
72.5

Technical Specs

  • Architecture: text+image+video->text
  • Context Window: 1,000,000 tokens
  • Input Modalities: text

Hardware Requirements

  • API-only (no local hardware needed)

Pricing

Input Output Currency
2.00 / 1M tokens 6.00 / 1M tokens USD