Alibaba (Qwen), proprietary

# Qwen3.7 Max

> Qwen3.7 Max by Alibaba (Qwen), released May 2026. Ranked #42 of 354 with a Noometry Index of 51.5. API: $2.50 in / $7.50 out per M tokens. 1M context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/qwen3-7-max
- Last updated: 2026-10-10
- Title: Qwen3.7 Max Benchmarks, Price & Rank (October 2026)

Qwen3.7 Max by Alibaba (Qwen) ranks 42nd of 354 ranked models on the Noometry Index as of October 2026, with a score of 51.5. Its strongest category is multilingual, where it ranks 15th. API pricing starts at $2.50 per million input tokens and $7.50 per million output tokens, with a 1M-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #42 of 354
- **Index score:** 51.5
- **Evidence:** Confirmed 33 results
- **Provider:** [![](/logos/alibaba.svg) Alibaba (Qwen)](https://noometry.com/providers/alibaba)
- **Released:** May 19, 2026
- **Weights:** Proprietary
- **Reasoning:** Yes
- **Context window:** 1M
- **Max output:** 131K
- **Input price:** $2.50 / M
- **Output price:** $7.50 / M
- **Blended price:** $3.75 / M
- **Output speed:** Not measured
- **Value:** #166 of 219
- **Knowledge cutoff:** Unknown
- **Input:** text

## Category scores

Each category score combines every public result we have in that category.

Qwen3.7 Max category scores

1.  Coding 50.4
2.  Agentic & Tool Use 22.1
3.  Reasoning 49.2
4.  Math 62.4
5.  Knowledge 61.6
6.  Multilingual 56.9
7.  Instruction Following 76.7
8.  Long Context 45.4
9.  Writing & Preference 65.0
10.  020406080

Qwen3.7 Max category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 50.4 | #45 | 4 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 22.1 | #135 | 1 |
| [Reasoning](https://noometry.com/best/reasoning) | 49.2 | #38 | 9 |
| [Math](https://noometry.com/best/math) | 62.4 | #32 | 5 |
| [Knowledge](https://noometry.com/best/knowledge) | 61.6 | #28 | 3 |
| [Multilingual](https://noometry.com/best/multilingual) | 56.9 | #15 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 76.7 | #38 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 45.4 | #40 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 65.0 | #54 | 4 |

## Strengths and weaknesses

Categories where Qwen3.7 Max places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

Qwen3.7 Max: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Multilingual](https://noometry.com/best/multilingual) | 56.9 | +9.5 | #15 of 297, top 6% |
| [Knowledge](https://noometry.com/best/knowledge) | 61.6 | +24.3 | #28 of 314, top 9% |
| [Math](https://noometry.com/best/math) | 62.4 | +25.9 | #32 of 327, top 10% |

### Weakest categories

Qwen3.7 Max: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 22.1 | −8.3 | #135 of 154, top 88% |
| [Writing & Preference](https://noometry.com/best/writing) | 65.0 | +11.2 | #54 of 312, top 18% |
| [Long Context](https://noometry.com/best/long-context) | 45.4 | +4.5 | #40 of 296, top 14% |

## Closest competitors

The models ranked just above and below Qwen3.7 Max. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to Qwen3.7 Max
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [DeepSeek V4.1 Flash](https://noometry.com/models/deepseek-v4-1-flash) | #38 | 52.8 | $0.26 | — | [Compare](https://noometry.com/compare/deepseek-v4-1-flash-vs-qwen3-7-max) |
| [GPT-5.2 Pro](https://noometry.com/models/gpt-5-2-pro) | #39 | 52.3 | $57.75 | — | [Compare](https://noometry.com/compare/gpt-5-2-pro-vs-qwen3-7-max) |
| [Gemini 3 Flash Preview](https://noometry.com/models/gemini-3-flash-preview) | #40 | 52.3 | $1.13 | — | [Compare](https://noometry.com/compare/gemini-3-flash-preview-vs-qwen3-7-max) |
| [GLM-5.3-Flash](https://noometry.com/models/glm-5-3-flash) | #41 | 51.8 | $0.24 | — | [Compare](https://noometry.com/compare/glm-5-3-flash-vs-qwen3-7-max) |
| [Qwen3.6 Max Preview](https://noometry.com/models/qwen3-6-max-preview) | #43 | 51.5 | $2.92 | — | [Compare](https://noometry.com/compare/qwen3-6-max-preview-vs-qwen3-7-max) |
| [GLM-5.2](https://noometry.com/models/glm-5-2) | #44 | 51.1 | $2.15 | 23 | [Compare](https://noometry.com/compare/glm-5-2-vs-qwen3-7-max) |
| [GPT-5](https://noometry.com/models/gpt-5) | #45 | 50.9 | $3.44 | 2 | [Compare](https://noometry.com/compare/gpt-5-vs-qwen3-7-max) |
| [Muse Spark](https://noometry.com/models/muse-spark) | #46 | 50.6 | — | — | [Compare](https://noometry.com/compare/muse-spark-vs-qwen3-7-max) |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

### Coding

Qwen3.7 Max Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [SWE-bench Verified](https://noometry.com/benchmarks/swe-bench-verified) | 77.3% | #7 of 32, top 22% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-18 |
| [LMArena WebDev](https://noometry.com/benchmarks/arena-webdev) | 1515 | #43 of 113, top 39% |  | [LMArena](https://lmarena.ai/leaderboard/webdev) | 2026-10-08 |
| [SciCode](https://noometry.com/benchmarks/scicode) | 48.8% | #47 of 121, top 39% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1498 | #22 of 294, top 8% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [ALE-Bench](https://noometry.com/benchmarks/ale-bench) | 1,189 | #31 of 105, top 30% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

Qwen3.7 Max Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GBAEval](https://noometry.com/benchmarks/gbaeval) | 0.4% | #20 of 23, top 87% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Reasoning

Qwen3.7 Max Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [SimpleBench](https://noometry.com/benchmarks/simplebench) | 70.4% | #11 of 77, top 15% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [NYT Connections (extended)](https://noometry.com/benchmarks/nyt-connections) | 85.1% | #29 of 91, top 32% |  | [Lech Mazur benchmarks](https://github.com/lechmazur/nyt-connections) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 13.4% | #40 of 134, top 30% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 19% | #63 of 129, top 49% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [EBR-Bench](https://noometry.com/benchmarks/ebr-bench) | 9.5% | #20 of 24, top 84% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-25 |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1483 | #28 of 297, top 10% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 32% | #25 of 74, top 34% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-07-28 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 26% |  | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 92.3% | #28 of 151, top 19% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 44% | #37 of 125, top 30% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 153.68 | #39 of 213, top 19% |  | [Epoch AI](https://epoch.ai/eci) | 2026-05-19 |

### Math

Qwen3.7 Max Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 64.6% | #33 of 81, top 41% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-13 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 34.1% | #25 of 63, top 40% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-06-13 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 95.6% | #35 of 173, top 21% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [ProofBench](https://noometry.com/benchmarks/proofbench) | 26% | #44 of 77, top 58% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1490 | #18 of 285, top 7% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Knowledge

Qwen3.7 Max Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 90.9% | #31 of 186, top 17% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-07 |
| [SimpleQA Verified](https://noometry.com/benchmarks/simpleqa-verified) | 55.8% | #19 of 77, top 25% |  | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-27 |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1488 | #34 of 273, top 13% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multilingual

Qwen3.7 Max Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1474 | #15 of 297, top 6% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1530 | #14 of 285, top 5% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1484 | #16 of 283, top 6% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

Qwen3.7 Max Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1460 | #34 of 298, top 12% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

Qwen3.7 Max Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1482 | #19 of 291, top 7% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

Qwen3.7 Max Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1476 | #19 of 297, top 7% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1449 | #29 of 295, top 10% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [EQ-Bench 4](https://noometry.com/benchmarks/eqbench-4) | 1110 | #23 of 28, top 83% |  | [EQ-Bench](https://eqbench.com/) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1481 | #18 of 295, top 7% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

Qwen3.7 Max API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [alibaba](https://www.alibabacloud.com/help/en/model-studio/models) | $2.50 | $7.50 | $0.50 | 2026-10-10 |
| [deepinfra](https://deepinfra.com/models) | $2.50 | $7.50 | $0.50 | 2026-10-10 |
| [openrouter](https://openrouter.ai/qwen/qwen3.7-max) | $1.48 | $4.42 | $0.29 | 2026-10-10 |
| [together](https://docs.together.ai/docs/serverless-models) | $1.25 | $3.75 | $0.13 | 2026-10-10 |

[All Alibaba (Qwen) API prices →](https://noometry.com/llm-pricing/alibaba) [Estimate your cost →](https://noometry.com/tools/cost-calculator)

## Compare Qwen3.7 Max

-   [Qwen3.7 Max vs Qwen3 Max](https://noometry.com/compare/qwen3-7-max-vs-qwen3-max)
-   [Qwen3.7 Max vs GLM-5.3-Flash](https://noometry.com/compare/glm-5-3-flash-vs-qwen3-7-max)
-   [Qwen3.7 Max vs Qwen3.6 Max Preview](https://noometry.com/compare/qwen3-6-max-preview-vs-qwen3-7-max)
-   [Qwen3.7 Max vs Gemini 3 Flash Preview](https://noometry.com/compare/gemini-3-flash-preview-vs-qwen3-7-max)
-   [Qwen3.7 Max vs GLM-5.2](https://noometry.com/compare/glm-5-2-vs-qwen3-7-max)
-   [Qwen3.7 Max vs GPT-5.2 Pro](https://noometry.com/compare/gpt-5-2-pro-vs-qwen3-7-max)
-   [Qwen3.7 Max vs GPT-5](https://noometry.com/compare/gpt-5-vs-qwen3-7-max)
-   [Qwen3.7 Max vs GPT-6 Astra](https://noometry.com/compare/gpt-6-astra-vs-qwen3-7-max)
-   [Qwen3.7 Max vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-qwen3-7-max)
-   [Qwen3.7 Max vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-qwen3-7-max)
-   [Qwen3.7 Max vs Kimi K3](https://noometry.com/compare/kimi-k3-vs-qwen3-7-max)
-   [Qwen3.7 Max vs Grok 4.6](https://noometry.com/compare/grok-4-6-vs-qwen3-7-max)
-   [Qwen3.7 Max vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-qwen3-7-max)
-   [Qwen3.7 Max vs Muse Spark 1.3](https://noometry.com/compare/muse-spark-1-3-vs-qwen3-7-max)

## Other Alibaba (Qwen) models

-   [Qwen3.8 Max](https://noometry.com/models/qwen3-8-max)56.8
-   [Qwen3.6 Max Preview](https://noometry.com/models/qwen3-6-max-preview)51.5
-   [Qwen3.6 Plus](https://noometry.com/models/qwen3-6-plus)47.5
-   [Qwen3.5 397B-A17B](https://noometry.com/models/qwen3-5-397b-a17b)46.0
-   [Qwen3.8 27B](https://noometry.com/models/qwen3-8-27b)46.0
-   [Qwen3.5 Max Preview](https://noometry.com/models/qwen3-5-max-preview)45.3
-   [Qwen3.7 Plus](https://noometry.com/models/qwen3-7-plus)45.3
-   [Qwen3 Max](https://noometry.com/models/qwen3-max)43.7

## Frequently asked questions

### How good is Qwen3.7 Max?

Qwen3.7 Max by Alibaba (Qwen) ranks 42nd of 354 ranked models on the Noometry Index as of October 2026, with a score of 51.5. Its strongest category is multilingual, where it ranks 15th. API pricing starts at $2.50 per million input tokens and $7.50 per million output tokens, with a 1M-token context window.

### How much does Qwen3.7 Max cost?

Qwen3.7 Max costs $2.50 per million input tokens and $7.50 per million output tokens on Alibaba (Qwen)'s own API, with cached input at $0.50.

### What is Qwen3.7 Max's context window?

Qwen3.7 Max accepts up to 1M tokens of input and can write up to 131K tokens in one response.

### Is Qwen3.7 Max open source?

No. Qwen3.7 Max is proprietary and available only through Alibaba (Qwen)'s API and partner platforms.

### What are Qwen3.7 Max's strengths and weaknesses?

Relative to other ranked models, Qwen3.7 Max places best in multilingual, knowledge, math and lowest in agentic & tool use, writing & preference, long context.

### What is Qwen3.7 Max best at?

Its best category is multilingual, where it ranks 15th on Noometry.

### Cite this page

Noometry. (2026). Qwen3.7 Max benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/qwen3-7-max

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/qwen3-7-max.md).