Qwen: Qwen2.5 VL 32B Instruct
Qwen's Qwen2.5 VL 32B Instruct is a vision-language model with reasonable MMLU-Pro scores, but limited benchmark coverage and accessibility considerations for UK businesses temper its appeal; best suited to teams specifically needing strong visual understanding at a moderate price point.
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
Qwen2.5-VL-32B is a multimodal vision-language model fine-tuned through reinforcement learning for enhanced mathematical reasoning, structured outputs, and visual problem-solving capabilities. It excels at visual analysis tasks, including object recognition, textual..
Capabilities
Architecture
| Modality | Text + Image → Text |
| Tokenizer | Qwen |
| Parameters | 32B |
Benchmark Scores
Intelligence
Technical
Benchmark data from Artificial Analysis and Hugging Face
How does Qwen: Qwen2.5 VL 32B Instruct stack up?
Compare side-by-side with other efficient models.
Model Information
| OpenRouter ID |
qwen/qwen2.5-vl-32b-instruct
|
| Provider | qwen |
| Release Date | March 24, 2025 |
| Context Length | 128,000 tokens |
| Status | Active |
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.20 | $0.000200 |
| Output | $0.60 | $0.000600 |
Live Performance
Live endpoint metrics — refreshed every 30 minutes.
Leaderboard Categories
External Resources
Explore Related Models
Data sourced from OpenRouter API, Artificial Analysis and Hugging Face Open LLM Leaderboard. Scores are editorially curated by our team.
Last updated: April 15, 2026 8:53 pm