Qwen: Qwen3 VL 32B Instruct
Qwen3 VL 32B Instruct is a capable vision-language model at a very competitive price, with reasonable MMLU Pro and math scores for its size. However, its overall intelligence and agentic benchmarks remain modest, making it better suited to structured visual tasks than complex reasoning or autonomous workflows.
Assessment date: March 14, 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
Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video. With 32 billion parameters, it combines deep visual perception with advanced text comprehension, enabling fine-grained spatial reasoning, document and scene analysis, and long-horizon video understanding.Robust OCR in 32 languages, and enhanced multimodal fusion through Interleaved-MRoPE and DeepStack architectures. Optimized for agentic interaction and visual tool use, Qwen3-VL-32B delivers state-of-the-art performance for complex real-world multimodal tasks.
Capabilities
Architecture
| Modality | Text + Image → Text |
| Tokenizer | Qwen |
| Parameters | 32B |
Performance Indices
Source: Artificial Analysis
Benchmark Scores
Evaluations
Benchmark data from Artificial Analysis and Hugging Face
Model Information
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.10 | $0.000104 |
| Output | $0.42 | $0.000416 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
