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DeepSeek-V3.2 Thinking vs Minimax M 2.5
Comprehensive side-by-side LLM comparison
Minimax M 2.5 leads with 7.1% higher average benchmark score. Minimax M 2.5 offers 68.1K more tokens in context window than DeepSeek-V3.2 Thinking. Minimax M 2.5 is $1.24 cheaper per million tokens. Overall, Minimax M 2.5 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3.2-Exp (DeepSeek-V3.2 Thinking), released by DeepSeek in September 2025, is the experimental preview release of the DeepSeek-V3.2 model featuring 685 billion total parameters and integrated thinking capabilities. It introduced the architecture and training approaches that became the foundation of the final V3.2 release, including thinking in tool-use and hybrid reasoning modes.
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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.
4 months newer
DeepSeek-V3.2 Thinking
DeepSeek
2025-09-29
Minimax M 2.5
MiniMax
2026-02-13
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.2 Thinking
Input:$0.55
Output:$2.19
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Minimax M 2.5
Input:$0.30
Output:$1.20($1.24 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek-V3.2 Thinking
Average Score:73.1%
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Minimax M 2.5
Average Score:80.2%(+7.1%)
Performance comparison across key benchmark categories
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DeepSeek-V3.2 Thinking
Coding73.1%
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Minimax M 2.5
Coding80.2%(+7.1%)
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.2 Thinking
1 providers
DeepSeek
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Minimax M 2.5
1 providers
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DeepSeek-V3.2 Thinking
Avg Score:73.1%
Providers:1
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Minimax M 2.5
Avg Score:80.2%(+7.1%)
Providers:1