Comprehensive side-by-side LLM comparison
Gemini 3.1 Pro offers 913.4K more tokens in context window than MiniMax M2.1. MiniMax M2.1 is $12.70 cheaper per million tokens. Gemini 3.1 Pro supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Google DeepMind
Gemini 3.1 Pro is a multimodal language model from Google DeepMind, released in preview in February 2026 as a point-version upgrade to Gemini 3 Pro focused on improving reasoning depth, factual grounding, and coding and agentic task performance. The model accepts text, images, video, audio, and PDFs as inputs across a 1M token context window, extending the multimodal breadth of the Gemini 3 series with a companion endpoint specifically optimized for custom tool use in agentic pipelines. Google describes it as built to refine the reliability and performance of the Gemini 3 Pro series, reflecting an incremental engineering iteration rather than an architectural overhaul.
MiniMax
MiniMax M2.1, released by MiniMax on December 23, 2025, is a large language model with approximately 230 billion parameters featuring strong multi-language programming capabilities and an industry-leading multilingual coding profile. It features a 196K token context window and is optimized for complex real-world software engineering tasks across Rust, Java, Golang, C++, TypeScript, and other languages. M2.1 targets agentic coding workflows and applications requiring production-grade programming across diverse language environments.
1 month newer
MiniMax M2.1
MiniMax
2025-12-23

Gemini 3.1 Pro
Google DeepMind
2026-02-19
Cost per million tokens (USD)
Gemini 3.1 Pro
MiniMax M2.1
Context window and performance specifications
Gemini 3.1 Pro
2025-01
Available providers and their performance metrics
Gemini 3.1 Pro
MiniMax M2.1
Gemini 3.1 Pro
MiniMax M2.1
Gemini 3.1 Pro
MiniMax M2.1
MiniMax