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
Qwen2.5-14B-Instruct is a 14-billion-parameter language model from Alibaba released in September 2024 within the Qwen2.5 family, occupying the mid-tier of the series between efficiency-focused small models and the high-capability 72B flagship. Trained on 18 trillion tokens with emphasis on instruction alignment, code understanding, and multilingual reasoning, it offers a strong performance-to-compute ratio for developers who need more capability than 7B but cannot serve 32B or larger models. The model supports 128K context windows and structured output generation out of the box.
Qwen2.5 14B Instruct
Alibaba / Qwen
2024-09-19
Context window and performance specifications
Available providers and their performance metrics
Llama 4 Behemoth
Together AI
Qwen2.5 14B Instruct
Llama 4 Behemoth
Qwen2.5 14B Instruct
Llama 4 Behemoth
Qwen2.5 14B Instruct