Comprehensive side-by-side LLM comparison
Gemini 3 Pro leads with 2.5% higher average benchmark score. Gemini 3 Pro offers 804.1K more tokens in context window than Minimax M 2.5. Minimax M 2.5 is $21.00 cheaper per million tokens. Gemini 3 Pro supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Google DeepMind
Gemini 3 Pro, released by Google in November 2025, is a large language model from the Gemini 3 family designed for complex reasoning, broad world knowledge, and multi-step problem solving. It features a 1M token context window, 64K maximum output tokens, and native multimodal input including text, images, audio, and video. Gemini 3 Pro targets research-grade reasoning, advanced data analysis, and applications requiring comprehensive understanding across diverse input formats.
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.
2 months newer

Gemini 3 Pro
Google DeepMind
2025-11-18
Minimax M 2.5
MiniMax
2026-02-13
Cost per million tokens (USD)
Gemini 3 Pro
Minimax M 2.5
Context window and performance specifications
Average performance across 2 common benchmarks
Gemini 3 Pro
Minimax M 2.5
Performance comparison across key benchmark categories
Gemini 3 Pro
Minimax M 2.5
Available providers and their performance metrics
Gemini 3 Pro
Google Cloud Vertex AI
Minimax M 2.5
Gemini 3 Pro
Minimax M 2.5
Gemini 3 Pro
Minimax M 2.5
MiniMax