Qwen: Qwen3.5 397B A17B
Qwen3.5 397B A17B is a strong all-round model with excellent instruction-following, multimodal support including video, a high agentic score, and very competitive pricing — though businesses should factor in regional accessibility when considering it for production use.
Assessment date: April 4, 2026
Our methodology takes into account a range of factors including pricing, functionality, capabilities, benchmark performance, and real-world applicability. Rankings are reviewed and updated regularly as new models are released. Issues with our rankings? Contact us
Performance Profile
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.
Capabilities
Architecture
| Modality | Text + Image + Video → Text |
| Tokenizer | Qwen3 |
| Parameters | 397B |
Performance Indices
Source: Artificial Analysis
Benchmark Scores
Intelligence
Technical
Content
Benchmark data from Artificial Analysis and Hugging Face
Model Information
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.39 | $0.000390 |
| Output | $2.34 | $0.002340 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
