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Model details

Qwen3.7 Max

Qwen3.7 Max is positioned as a versatile agent foundation model for the agent era, designed to handle a wide spectrum of work that goes well beyond single-turn chat. Its design intent centers on sustained autonomous behavior, blending strong coding ability with office productivity and long-horizon reasoning across many sequential tool calls. The model continues the Qwen line of MoE architectures with updated expert routing and an attention mechanism refined from the prior generation, paired with an unusually wide context window that supports deep, multi-step workflows. In practice, it is meant to feel less like a conversational assistant and more like a reliable operator that can take on real engineering and automation tasks end to end, from frontend prototyping to multi-file software projects to spreadsheet-driven office work, while remaining compatible with several popular agent frameworks without requiring framework-specific tuning.

The model's strengths show up clearly in its benchmark profile, where it posts 80.4% on SWE-Bench Verified and 78.3% on SWE-Multilingual for agentic coding, 69.7 on Terminal-Bench 2.0-Terminus for terminal-style execution, and 60.8% on MCP-Mark with 76.4% on MCP-Atlas for tool orchestration. It also reaches 87.0% on SpreadSheetBench-v1 for office-style automation, alongside 92.4% on GPQA Diamond, 97.1% on HMMT 2026 Feb, and 79.1% on IFBench, signaling serious scientific reasoning and instruction-following ability. A highlight of the release is a reported ~35-hour fully autonomous run covering over a thousand tool calls, in which the model produced a 10x kernel speedup on unseen hardware, illustrating how the architecture and training choices translate into extended, coherent agentic behavior. With explicit prompt caching for efficient repeated context use, Qwen3.7 Max fits naturally into production pipelines that need to amortize cost over long agent traces, and it looks forward to a near future where autonomous, multi-step AI workers become a standard layer of software development and office operations.

Alibaba Token Plan (China)qwen3.7-maxqwen

Quick Info

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Provider
Alibaba Token Plan (China)
Model key
qwen3.7-max
Release date
May 21, 2026
Last updated
May 21, 2026
Input modalities
Output modalities
Capabilities

Cost

A provider subscription or plan supersedes token-based pricing for this model.

Limits

Output tokens
131,072 tokens
Context window
1,000,000 tokens

Latest news about Qwen3.7 Max

Alibaba Token Plan (China)

CoverageBenchmark

DataCamp's feature article (May 22, 2026) positions Qwen3.7-Max as Alibaba's latest proprietary flagship, a closed-weight, API-accessible model available through Alibaba Cloud Model Studio with a 1 million token context window and text-only input/output, framed as a "versatile agent foundation" rather than a general-pu Headline benchmark comparisons include GPQA Diamond 92.4 (beating Claude Opus 4.6 Max's 91.3), Apex reasoning 44.5 (versus DeepSeek V4 Pro's 38.3), and a 35-hour autonomous kernel-optimization run in which Qwen3.7-Max made 1,158 tool calls and achieved a 10x geometric mean speedup over the Triton reference implementati

Alibaba Token Plan (China)

CoverageBenchmark

The llm-stats.com leaderboard page (dated May 19, 2026) provides independent placement data for Qwen3.7-Max, ranking it 26th overall on the composite LLM Stats Score and assigning top-tier capability placements: S-tier (Top 2%) in Finance, Legal, and Healthcare, and A-tier (Top 10%) in Math, 3D, Chat, and Websites. Mid Cost-efficiency data places Qwen3.7-Max at a blended $1.37 per million tokens on the llm-stats chart, with an LLM Stats composite score of 45.6. The scorecard cites internal Qwen benchmarks including QwenSVG (rank 2, score 1608/2000, methodology: internal SVG generation benchmark using BT/Elo rating from auto-rendered

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