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
Qwen2.5-72B-Instruct is the flagship of Alibaba's Qwen2.5 series, a 72-billion-parameter open-weight model released in September 2024 after training on 18 trillion tokens spanning code, mathematics, and multilingual text. It offers strong generalist performance across coding, instruction-following, and structured reasoning while remaining fully open-weight under Apache 2.0 — a combination that made it a widely referenced model in open-source evaluations and community benchmarking. The 128K context window and built-in structured output support made it a common choice for document analysis and multi-step agentic pipeline development.
Qwen2.5 72B Instruct
Alibaba / Qwen
2024-09-19
Context window and performance specifications
Available providers and their performance metrics
Llama 4 Behemoth
Together AI
Qwen2.5 72B Instruct
Llama 4 Behemoth
Qwen2.5 72B Instruct
Llama 4 Behemoth
Qwen2.5 72B Instruct