Comprehensive side-by-side LLM comparison
Qwen2.5-VL 32B Instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Moonshot AI
Kimi K2, released by Moonshot AI on July 11, 2025, is an open-weight Mixture-of-Experts large language model with 1 trillion total parameters and 32 billion active parameters per inference. It features a 256K token context window (expanded from 128K in an September 2025 update) and demonstrated strong performance on agentic coding benchmarks. Kimi K2 targets software engineering agents, tool-use workflows, and open-source deployments under a modified MIT license.
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.
4 months newer
Qwen2.5-VL 32B Instruct
Alibaba / Qwen
2025-03-01
Kimi K2
Moonshot AI
2025-07-11
Context window and performance specifications
Available providers and their performance metrics
Kimi K2
Moonshot AI
Qwen2.5-VL 32B Instruct
Kimi K2
Qwen2.5-VL 32B Instruct
Kimi K2
Qwen2.5-VL 32B Instruct