Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
MiniMax
MiniMax M2.5 is a large language model from MiniMax extensively trained with reinforcement learning across hundreds of thousands of complex real-world environments. It targets agentic tool use, coding automation, and office productivity tasks, with strong results on software engineering and web browsing benchmarks. M2.5 represents the next generation of MiniMax's M-series models optimized for production agentic workloads.
Alibaba / Qwen
Qwen2.5-14B-Instruct is a 14-billion-parameter language model from Alibaba released in September 2024 within the Qwen2.5 family, occupying the mid-tier of the series between efficiency-focused small models and the high-capability 72B flagship. Trained on 18 trillion tokens with emphasis on instruction alignment, code understanding, and multilingual reasoning, it offers a strong performance-to-compute ratio for developers who need more capability than 7B but cannot serve 32B or larger models. The model supports 128K context windows and structured output generation out of the box.
1 year newer
Qwen2.5 14B Instruct
Alibaba / Qwen
2024-09-19
Minimax M 2.5
MiniMax
2026-02-13
Context window and performance specifications
Available providers and their performance metrics
Minimax M 2.5
MiniMax
Qwen2.5 14B Instruct
Minimax M 2.5
Qwen2.5 14B Instruct
Minimax M 2.5
Qwen2.5 14B Instruct