Comprehensive side-by-side LLM comparison
Llama 4 Behemoth supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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.
Alibaba / Qwen
Qwen2.5-Coder-7B-Instruct is a 7-billion-parameter code-specialized model from Alibaba, released in November 2024 as part of the Qwen2.5-Coder family, trained on a curated corpus spanning 92 programming languages with emphasis on code generation, debugging, and fill-in-the-middle completion. Built on the Qwen2.5 architecture, it extends the base series' improvements in instruction-following and long-context handling to coding-specific tasks within a compact deployable footprint. It became popular for integration into IDE extensions, CI pipelines, and self-hosted code assistant tools.
Qwen2.5-Coder 7B Instruct
Alibaba / Qwen
2024-11-12
Context window and performance specifications
Available providers and their performance metrics
Llama 4 Behemoth
Together AI
Qwen2.5-Coder 7B Instruct
Llama 4 Behemoth
Qwen2.5-Coder 7B Instruct
Llama 4 Behemoth
Qwen2.5-Coder 7B Instruct