Alibaba Frontier Available in FlowHunt

Qwen 3.7-Max

Qwen 3.7-Max is a top-tier frontier AI model, developed by Alibaba and released in May 2026. It is a proprietary closed-weight model, available through the Alibaba API. The 1M-token context window is large enough to hold entire codebases, lengthy technical documents, or extended agentic sessions without truncation.

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Qwen 3.7-Max was released on May 20, 2026 as the top model in Alibaba’s Qwen 3 generation, introducing what Alibaba called a ’thinking mode’ — an extended chain-of-thought reasoning capability that can be toggled per query. In thinking mode, the model runs an internal deliberation step before producing its final answer, improving performance substantially on multi-step reasoning tasks. Combined with a 1M context window and competitive API pricing, it established itself as the primary Frontier-tier alternative for cost-conscious enterprise teams.
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Benchmarks

Each score appears once, with its rank among tracked models and who measured it.

Compared with Frontier peers on the same scale
  • Qwen 3.7-Maxthis model
  • GPT-6.1 Solthis model leads on 0 of 3
  • Claude Opus 5.5this model leads on 0 of 4
Verified independent evaluator, counted in the ranking Self-reported published by Alibaba, shown but not ranked
Overall

AA Intelligence Index

Independent composite of agent, coding, knowledge and science tests by Artificial Analysis (v4).

Source ↗

Qwen 3.7-Max 29.5 GPT-6.1 Sol 51.8 Claude Opus 5.5 57.6
#30of 45 Verified
Coding

SWE-bench Pro

Real issues across several languages and large codebases.

Qwen 3.7-Max 60.6% GPT-6.1 Sol No score Claude Opus 5.5 89.9%
Not ranked Self-reported

SWE-bench Verified

500 verified GitHub issues. Saturated at the frontier.

Source ↗Also: Self-reported 80.4%

Qwen 3.7-Max 68.8% GPT-6.1 Sol No score Claude Opus 5.5 No score
#20of 22 Verified
Agents

Terminal-Bench 4.0

Multi-step professional tasks done by an agent in a command-line terminal.

Source ↗

Qwen 3.7-Max 1.5% GPT-6.1 Sol 56.1% Claude Opus 5.5 59.6%
#29of 36 Verified
Reasoning

Humanity's Last Exam

Expert-written questions across 100+ subjects, no tools.

Source ↗

Qwen 3.7-Max 40.5% GPT-6.1 Sol 52.9% Claude Opus 5.5 61.4%
#23of 44 Verified

GPQA Diamond

Graduate-level science questions that search cannot answer.

Source ↗Also: Self-reported 92.4%

Qwen 3.7-Max 92.3% GPT-6.1 Sol No score Claude Opus 5.5 No score
#14of 37 Verified

What to Use Qwen 3.7-Max For

Software Engineering

It resolves real GitHub issues, writes production-quality code across multiple languages, and handles multi-step agentic coding workflows — a strong choice for AI-assisted software development teams.

Scientific & Technical Reasoning

Use it for scientific literature synthesis, hypothesis evaluation, medical and legal Q&A, and multi-discipline research tasks where deep domain knowledge matters.

Long-Document & Codebase Analysis

With a 1M-token context window, Qwen 3.7-Max can ingest entire software repositories, long legal contracts, book-length research reports, or extensive conversation histories in a single prompt — enabling deep document Q&A, cross-file codebase reasoning, and comprehensive summarisation without chunking heuristics or RAG pipelines.

Competitive Programming

At this level it handles advanced data structures, graph algorithms, and interview-level challenges with high reliability.

Strengths and limitations

Strengths

  • Strong software engineering
  • Graduate-level science reasoning
  • Competitive programming
  • Composite intelligence
  • Very long documents and large codebases (1M context)

Limitations

  • Closed-weight — cannot be self-hosted or fine-tuned on private data

Use it in FlowHunt

Use Qwen 3.7-Max in any flow, next to your own tools and knowledge sources.

  1. 1Open a flow, or create one from a template
  2. 2Add an AI Agent or Generator component
  3. 3Pick Qwen 3.7-Max in the model selector

Related AI Models

About Alibaba Hangzhou, China · Founded 1999 · qwenlm.github.io

Alibaba Group is one of China's largest and most diverse technology conglomerates, founded in 1999 by Jack Ma and headquartered in Hangzhou. Through its DAMO Academy and Tongyi Lab, Alibaba has become a major force in large language model development with the Qwen (Tongyi Qianwen) family. The Qwen 3.7 generation, released in mid-2026, marked Alibaba's transition from domestic deployments to international benchmark competitiveness, and the Qwen 3.8 generation followed in 2026. Alibaba's AI strategy is defined by open-weight releases as a counterbalance to US API-only models, integration of generative AI across its cloud and e-commerce businesses, and heavy investment in AI infrastructure across its Alibaba Cloud division.

qwenlm.github.io ↗

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Compare every tracked model on coding, agent and reasoning benchmarks, with each score marked verified or self-reported.

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Frequently asked questions

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