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Llama 4 Behemoth vs Qwen2.5-Coder 32B Instruct
Comprehensive side-by-side LLM comparison
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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Alibaba / Qwen
Qwen2.5-Coder-32B-Instruct is a 32-billion-parameter code-specialized model from Alibaba, released in November 2024 and trained on a large corpus spanning 92 programming languages including C, Python, Java, Rust, and domain-specific languages. The model was designed to provide competitive code generation, repair, and reasoning capabilities as an open-weight alternative for developers building code assistant tools and automated review pipelines. Its 128K context window enables whole-file and multi-file code comprehension, making it particularly suited for complex repository-level tasks.
Qwen2.5-Coder 32B Instruct
Alibaba / Qwen
2024-11-12
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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Qwen2.5-Coder 32B Instruct
0 providers
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Llama 4 Behemoth
Avg Score:0.0%
Providers:1
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Qwen2.5-Coder 32B Instruct
Avg Score:0.0%
Providers:0