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Gemini 3.1 Pro vs Minimax M 2.5
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Gemini 3.1 Pro offers 910.0K more tokens in context window than Minimax M 2.5. Minimax M 2.5 is $12.50 cheaper per million tokens. Gemini 3.1 Pro supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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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.
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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.
6 days newer
Minimax M 2.5
MiniMax
2026-02-13
Gemini 3.1 Pro
Google DeepMind
2026-02-19
Pricing Comparison
Cost per million tokens (USD)
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Gemini 3.1 Pro
Input:$2.00
Output:$12.00
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Minimax M 2.5
Input:$0.30
Output:$1.20($12.50 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Gemini 3.1 Pro
Average Score:80.6%(+0.4%)
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Minimax M 2.5
Average Score:80.2%
Performance comparison across key benchmark categories
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Gemini 3.1 Pro
Coding80.6%(+0.4%)
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Minimax M 2.5
Coding80.2%
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Knowledge Cutoff
Training data recency comparison
Gemini 3.1 Pro
2025-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 3.1 Pro
1 providers
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Minimax M 2.5
1 providers
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Gemini 3.1 Pro
Avg Score:80.6%(+0.4%)
Providers:1
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Minimax M 2.5
Avg Score:80.2%
Providers:1