Intelligence index
Outperforms 57% of compared models
Qwen3.5 397B A17B
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.
- Input / output price
- $0.5/$3.6per 1M tokens
- Context
- 262K
- Released
- 2026-02-16
Pricing
Artificial Analysis
Explore rankingsDesign Arena
Elo scores and win rates across design and agent tasks.
Category performance
1,000-1,500 EloModel Arena
SVG
1136Elo
Win rate 56.1%
3D
1158Elo
Win rate 56.7%
Code Categories
1178Elo
Win rate 52.6%
Data Visualization
1175Elo
Win rate 53.2%
Website
1189Elo
Win rate 52.5%
UI Component
1158Elo
Win rate 51.4%
Game Development
1140Elo
Win rate 50.2%
Related Models
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qwenQwen3.8 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.
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- Max output
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- Released
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- Input
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- Output
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- Cache read
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Qwen3.8 2.4T A95B
qwenQwen3.8 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
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- Max output
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- Released
- 2026-08-12
- Input
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- Output
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- Cache read
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Qwen3.8 27B
qwenQwen3.8 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
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- Input
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- Output
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- Cache read
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