Comprehensive side-by-side LLM comparison
Llama-3.3 Nemotron Super 49B leads with 3.1% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
NVIDIA
Llama-3.3-Nemotron-Super-49B-v1 is a 49-billion-parameter model from NVIDIA, fine-tuned from Meta's Llama 3.3 using NVIDIA's Nemotron post-training pipeline that combines supervised fine-tuning with reinforcement learning to enhance reasoning, instruction alignment, and complex problem-solving. The Super tier in the Nemotron family represents a mid-range capability level — positioned above the Nano series and below the Ultra 253B flagship — offering a balance between high-quality outputs and manageable inference infrastructure requirements. Released open-weight on HuggingFace with NVIDIA NIM support, it targets teams with multi-GPU setups who need strong reasoning capability without the scale of the Ultra model.
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.
5 months newer
Qwen2.5 72B Instruct
Alibaba / Qwen
2024-09-19

Llama-3.3 Nemotron Super 49B
NVIDIA
2025-03-01
Average performance across 1 common benchmarks
Llama-3.3 Nemotron Super 49B
Qwen2.5 72B Instruct
Performance comparison across key benchmark categories
Llama-3.3 Nemotron Super 49B
Qwen2.5 72B Instruct
Available providers and their performance metrics
Llama-3.3 Nemotron Super 49B
Qwen2.5 72B Instruct
Llama-3.3 Nemotron Super 49B
Qwen2.5 72B Instruct