Comprehensive side-by-side LLM comparison
Qwen2.5-VL 32B Instruct leads with 2.6% higher average benchmark score. Qwen2.5-VL 32B Instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Alibaba / Qwen
Qwen2.5-VL-32B-Instruct is a 32-billion-parameter vision-language model from Alibaba, extending the Qwen2.5 architecture with multimodal capabilities for understanding images, documents, charts, and video frames alongside text. The model was designed for tasks requiring deep visual reasoning — such as document parsing, table extraction, and spatial understanding — with performance that made it a practical choice for document intelligence and visual data analysis workflows. As an open-weight model, it became a widely adopted foundation for fine-tuning domain-specific multimodal applications.
Alibaba / Qwen
Qwen3-235B-A22B, released by Alibaba's Qwen team on April 28, 2025, is a Mixture-of-Experts large language model with 235 billion total parameters and 22 billion active parameters per inference. It features a 256K token context window, hybrid thinking capabilities (both reasoning and direct generation modes), and was trained on 36 trillion tokens across 119 languages. Qwen3-235B targets complex reasoning, multilingual tasks, and open-source deployments under the Apache 2.0 license.
1 month newer
Qwen2.5-VL 32B Instruct
Alibaba / Qwen
2025-03-01
Qwen3-235B-A22B
Alibaba / Qwen
2025-04-28
Context window and performance specifications
Average performance across 1 common benchmarks
Qwen2.5-VL 32B Instruct
Qwen3-235B-A22B
Performance comparison across key benchmark categories
Qwen2.5-VL 32B Instruct
Qwen3-235B-A22B
Available providers and their performance metrics
Qwen2.5-VL 32B Instruct
Qwen3-235B-A22B
OpenRouter
Qwen2.5-VL 32B Instruct
Qwen3-235B-A22B
Qwen2.5-VL 32B Instruct
Qwen3-235B-A22B