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Llama 4 Behemoth vs MiniMax M2.1
Comprehensive side-by-side LLM comparison
Llama 4 Behemoth offers 3.4K more tokens in context window than MiniMax M2.1. MiniMax M2.1 is $4.70 cheaper per million tokens. Llama 4 Behemoth supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Meta AI
Llama 4 Behemoth is a research-scale Mixture-of-Experts language model with approximately 2 trillion total parameters (288 billion active per inference), developed by Meta as a teacher model for the Llama 4 family. Available only in limited preview, it serves as the knowledge distillation source for Llama 4 Scout and Maverick. Behemoth targets research applications requiring the largest-scale open-weight model architecture from the Llama 4 generation.
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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.
MiniMax M2.1
MiniMax
2025-12-23
Pricing Comparison
Cost per million tokens (USD)
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Llama 4 Behemoth
Input:$3.00
Output:$3.00
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MiniMax M2.1
Input:$0.20
Output:$1.10($4.70 cheaper)
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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Llama 4 Behemoth
1 providers
Together AI
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MiniMax M2.1
1 providers
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Llama 4 Behemoth
Avg Score:0.0%
Providers:1
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MiniMax M2.1
Avg Score:0.0%
Providers:1