Qwen

Qwen 3.7 Max

QwenBalanced
ThinkingTool UseStructured Output

About this model

Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with particular strengths in coding, office and productivity tasks,...

Performance Tier

Balanced

Qwen 3.7 Max is a balanced model from Qwen : strong performance at a reasonable price.

Strong cost-performance ratio. Reliable for most professional use cases without premium pricing.

Pricing

This model is included in Elosia plans
Moderate

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

Typeper 1M tokens
Input (prompt)$1.48
Output (completion)$4.42
Cache read$0.295
Cache write$1.84

Capabilities

Context Length1.0M
Max Output Tokens131K
TokenizerQwen
Inputtext
Outputtext
Release DateMay 21, 2026

Benchmarks

General Intelligence
MMLU
Not reported
GPQA Diamond
92.4%
Mathematics
MATH-500
Not reported
AIME 2025
93.3%
Programming
HumanEval
Not reported
SWE-bench Verified
80.4%
SWE-bench Multilingual
78.3%
Reasoning
Humanity's Last Exam
41.4%
Agentic
SWE-bench Pro
60.6%
Terminal-Bench 2.0
69.7%

Where does Qwen 3.7 Max stand?

Compare its performance index against every other model.

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Recommended Use Cases

CodingAnalysisResearchGeneral ChatTranslation

Strengths

  • Agent model of the Qwen line, evaluated on real repository patches rather than isolated function completion
  • Scientific reasoning and competition mathematics are part of the reported suite, so the scope is not code alone
  • Agentic coding evaluated across several programming languages, not on a single-language repository set
  • Long-horizon command-line workflows covered as well, with terminal agentic tasks reported next to repository patches
  • Built-in thinking mode (enable_thinking / preserve_thinking) for chain-of-thought reasoning

Limitations

  • Alibaba's evaluation focuses on agentic and coding benchmarks: MMLU, MATH-500, HumanEval and LiveCodeBench are not part of the reported suite
  • Text input only, with no image or video accepted, and no parallel tool calls exposed
  • Closed weights with no published checkpoint, so no self-hosted deployment

Frequently asked questions

Resources

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