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AI123AI ModelsqwenQwen3.7 Max
Qwen3.7 Max

Qwen3.7 Max

qwen

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, and long-horizon autonomous execution. The model offers notable gains in coding and agentic performance over prior Qwen generations and supports explicit prompt caching for efficient repeated context use.

Modalities
TT
Input / output price
$1.48/$4.43per 1M tokens
Context
1.0M
Released
2026-05-21
PricingArtificial AnalysisDesign ArenaRelated Models

Pricing

Usage prices in USD. Token rates are per one million tokens; other billing units are shown with each charge.
InputOutputCache readCache write
$1.48/ 1M tokens$4.42/ 1M tokens$0.29/ 1M tokens$1.84/ 1M tokens

Artificial Analysis

Explore rankings
29.5

Intelligence index

Outperforms 77% of compared models

66.0

Coding index

Outperforms 75% of compared models

22.5

Agentic index

Outperforms 59% of compared models

Design Arena

Elo scores and win rates across design and agent tasks.

Category performance

1,000-1,500 Elo
3D: 1263; Asciiart: 1208; Code Categories: 1274; Data Visualization: 1276; Game Development: 1264; SVG: 1214; UI Component: 1264; Website: 12743D1263 EloAsciiart1208 EloCode Categories1274 EloData Visualization1276 EloGame Development1264 EloSVG1214 EloUI Component1264 EloWebsite1274 Elo

Model Arena

Asciiart

1208Elo

Win rate 53%

Data Visualization

1276Elo

Win rate 52.9%

SVG

1214Elo

Win rate 55.2%

Website

1274Elo

Win rate 54.5%

3D

1263Elo

Win rate 54.3%

Code Categories

1274Elo

Win rate 53.9%

Game Development

1264Elo

Win rate 52.7%

UI Component

1264Elo

Win rate 53.2%

Agent Arena

Godotgamedev

1187Elo

Win rate 55.7%

Htmlslides

1054Elo

Win rate 43.6%

Agenticgamedev

1125Elo

Win rate 46.1%

Python-pptxslides

1147Elo

Win rate 47.5%

Blender3d

1054Elo

Win rate 35%

Fullstack

1191Elo

Win rate 47.7%

Webapps

1208Elo

Win rate 48.8%

Androidnative

1157Elo

Win rate 48.5%

Mobile Apps

1157Elo

Win rate 45.3%

How Design Arena works

Related Models

Qwen3.8 Max (0902)

Qwen3.8 Max (0902)

qwen

Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team. It is a 2.4-trillion-parameter mixture-of-experts model that accepts text, image, and video input and returns text, with a 1M-token context window and reasoning enabled by default. This snapshot is post-trained for coding and agentic work, including multi-step software projects, multi-tool orchestration, and long-horizon task execution. It also targets chart reasoning, document parsing, and multimodal understanding over long documents and extended video. Tool calling, structured outputs, and configurable reasoning effort are supported.

Context
1.0M
Max output
131.1K
Released
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Input
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Output
$6/M
Cache read
$0.25/M
Qwen3.8 2.4T A95B

Qwen3.8 2.4T A95B

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Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of Qwen3.8 Max, with 95 billion active parameters out of 2.4 trillion total. It is suited for coding, research, complex reasoning, and agentic workflows.

Context
1.0M
Max output
909K
Released
2026-08-12
Input
$2/M
Output
$6/M
Cache read
$0.25/M
Qwen3.8 27B

Qwen3.8 27B

qwen

Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be enabled or disabled.

Context
1.0M
Max output
65.5K
Released
2026-08-14
Input
$0.039/M
Output
$1.25/M
Cache read
$0.0039/M
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