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DeepSeek-V3.2 vs Llama 4 Behemoth
Comprehensive side-by-side LLM comparison
Llama 4 Behemoth offers 68.1K more tokens in context window than DeepSeek-V3.2. DeepSeek-V3.2 is $4.63 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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DeepSeek
DeepSeek-V3.2, released by DeepSeek on December 1, 2025, is a large language model with 685 billion total parameters featuring integrated thinking in tool-use and support for both reasoning and direct generation modes. It features a 128K token context window and introduced large-scale agent training across 1,800+ environments. DeepSeek-V3.2 targets agentic workflows, complex instruction following, and coding tasks under an open MIT license.
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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.
DeepSeek-V3.2
DeepSeek
2025-12-01
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.2
Input:$0.27
Output:$1.10($4.63 cheaper)
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Llama 4 Behemoth
Input:$3.00
Output:$3.00
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.2
1 providers
DeepSeek
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Llama 4 Behemoth
1 providers
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DeepSeek-V3.2
Avg Score:0.0%
Providers:1
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Llama 4 Behemoth
Avg Score:0.0%
Providers:1