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DeepSeek-R1 vs Llama 4 Behemoth
Comprehensive side-by-side LLM comparison
Llama 4 Behemoth offers 68.1K more tokens in context window than DeepSeek-R1. DeepSeek-R1 is $3.26 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-R1, released by DeepSeek on January 20, 2025, is a large reasoning model with 671 billion total parameters (37 billion active in its MoE architecture) designed for extended chain-of-thought reasoning. It features a 128K token context window and demonstrated strong performance on mathematics, coding, and scientific reasoning benchmarks at its release. DeepSeek-R1 targets complex analytical tasks, competitive programming, and applications requiring deep deliberative reasoning 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-R1
DeepSeek
2025-01-20
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-R1
Input:$0.55
Output:$2.19($3.26 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-R1
1 providers
DeepSeek
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Llama 4 Behemoth
1 providers
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DeepSeek-R1
Avg Score:0.0%
Providers:1
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Llama 4 Behemoth
Avg Score:0.0%
Providers:1