Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
Google DeepMind
Gemini Diffusion is an experimental text and code generation model from Google DeepMind, announced at Google I/O in May 2025 as the first diffusion-based language model to achieve quality comparable to autoregressive models on standard benchmarks. Unlike transformer-based models that predict tokens sequentially left-to-right, it generates entire blocks of text by iteratively refining noise — the paradigm used in image and video generation models — enabling faster sampling speeds and stronger mid-generation error correction for code and mathematical editing tasks. At announcement it was available only as an experimental demo via waitlist, with no public API, marking it as a research milestone rather than a production deployment.
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.
8 months newer

Gemini Diffusion
Google DeepMind
2025-05-20
Minimax M 2.5
MiniMax
2026-02-13
Context window and performance specifications
Available providers and their performance metrics
Gemini Diffusion
Minimax M 2.5
MiniMax
Gemini Diffusion
Minimax M 2.5
Gemini Diffusion
Minimax M 2.5