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DeepSeek-V3.1 vs MiniMax M2.1
Comprehensive side-by-side LLM comparison
MiniMax M2.1 offers 64.7K more tokens in context window than DeepSeek-V3.1. Both models have similar pricing. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3.1, released by DeepSeek in August 2025, is a hybrid large language model with 671 billion total parameters (37 billion active) that unifies the capabilities of DeepSeek-V3 and DeepSeek-R1 in a single model. It features a 128K token context window and supports both direct generation and extended reasoning modes selectable via the chat template. DeepSeek-V3.1 targets general-purpose tasks, coding, and complex reasoning under an open MIT license.
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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.
4 months newer
DeepSeek-V3.1
DeepSeek
2025-08-21
MiniMax M2.1
MiniMax
2025-12-23
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.1
Input:$0.27
Output:$1.10
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MiniMax M2.1
Input:$0.20
Output:$1.10($0.07 cheaper)
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.1
1 providers
DeepSeek
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MiniMax M2.1
1 providers
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DeepSeek-V3.1
Avg Score:0.0%
Providers:1
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MiniMax M2.1
Avg Score:0.0%
Providers:1