Head-to-head · frontier vs frontier

Qwen3-Max vs Qwen3-Max Turbo: which model should you choose?

We compared Qwen3-Max and Qwen3-Max Turbo on price, context window and 12 benchmarks. Qwen3-Max Turbo has the stronger average benchmark score; Qwen3-Max Turbo is cheaper on a blended 3:1 basis.

Alibaba Cloud

Qwen3-Max

Qwen3-Max is a frontier model from Alibaba Cloud. It offers a 400,000-token context window, costs $17.37 per million input tokens and $94.30 per million output tokens, and averages 84.4 across the index's benchmark suite.

Input
$17.37 / 1M
Output
$94.30 / 1M
Context
400,000
Avg score
84.4
Open weights
No
Full Qwen3-Max page
Alibaba Cloud

Qwen3-Max Turbo

Qwen3-Max Turbo is a frontier model from Alibaba Cloud. It offers a 1,000,000-token context window, costs $17.70 per million input tokens and $63.95 per million output tokens, and averages 84.7 across the index's benchmark suite.

Input
$17.70 / 1M
Output
$63.95 / 1M
Context
1,000,000
Avg score
84.7
Open weights
No
Full Qwen3-Max Turbo page

Specification comparison

SpecQwen3-MaxQwen3-Max TurboEdge
Input price / 1M$17.37$17.70A
Output price / 1M$94.30$63.95B
Context window400,0001,000,000B
Max output4,096128,000B
Average score84.484.7B
Arena Elo1449.21456.9B
Open weightsNoNoTie

Benchmark comparison

Qwen3-Max wins 4, Qwen3-Max Turbo wins 8, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.

BenchmarkQwen3-MaxQwen3-Max TurboGapWinner
MMLU-Pro84.086.82.8Qwen3-Max Turbo
GPQA Diamond82.378.34.0Qwen3-Max
SWE-bench Verified73.375.92.6Qwen3-Max Turbo
HumanEval88.592.54.0Qwen3-Max Turbo
MATH-50089.791.92.2Qwen3-Max Turbo
AIME 202581.181.20.1Qwen3-Max Turbo
LiveCodeBench82.276.85.4Qwen3-Max
IFEval92.592.10.4Qwen3-Max
TruthfulQA83.486.32.9Qwen3-Max Turbo
HellaSwag92.990.82.1Qwen3-Max
MMMU78.778.80.1Qwen3-Max Turbo
Arena Elo1449.21456.97.7Qwen3-Max Turbo

Price analysis

On a blended 3:1 input-to-output basis, Qwen3-Max costs about $36.60 per million tokens and Qwen3-Max Turbo costs about $29.26. Qwen3-Max Turbo is roughly 20% cheaper than Qwen3-Max. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.

Qwen3-Max Turbo has the larger context window at 1,000,000 tokens, compared with 400,000 for Qwen3-Max. That matters for long documents, large codebases and multi-step agent traces.

Verdict

Across 12 shared benchmarks, Qwen3-Max wins 4, Qwen3-Max Turbo wins 8, and 0 are tied. On the index average, Qwen3-Max Turbo leads Qwen3-Max by 0.3 points (84.7 versus 84.4).

The price picture favours Qwen3-Max Turbo. The context picture favours Qwen3-Max Turbo. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.

If you need a single default, start with Qwen3-Max Turbo for quality-sensitive work, and check whether its price holds at your expected volume before committing.

Choose Qwen3-Max if

  • You prefer Alibaba Cloud's tooling or already use it.

Choose Qwen3-Max Turbo if

  • You want the higher average benchmark score in this index.
  • Unit cost matters and you want the cheaper blended price.
  • You need the larger 1,000,000-token context window.
  • You need the larger 128,000-token output limit.

FAQ

Is Qwen3-Max better than Qwen3-Max Turbo?

On the index average, Qwen3-Max Turbo leads Qwen3-Max by 0.3 points (84.7 versus 84.4). The better choice depends on price, context and your task. Qwen3-Max wins 4 benchmarks, Qwen3-Max Turbo wins 8.

Which is cheaper, Qwen3-Max or Qwen3-Max Turbo?

Qwen3-Max Turbo is cheaper on a blended 3:1 basis at about $29.26 per million tokens, versus $36.60 for Qwen3-Max.

Which has the larger context window?

Qwen3-Max Turbo has the larger context window at 1,000,000 tokens. Qwen3-Max has 400,000 tokens.

Are these models open weights?

Qwen3-Max is proprietary; Qwen3-Max Turbo is proprietary.

Which should I choose for production?

If you need a single default, start with Qwen3-Max Turbo for quality-sensitive work, and check whether its price holds at your expected volume before committing.

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