Comprehensive side-by-side LLM comparison
Llama-3.3 Nemotron Super 49B leads with 1.1% 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-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.
3 months newer
Qwen2.5-Coder 32B Instruct
Alibaba / Qwen
2024-11-12

Llama-3.3 Nemotron Super 49B
NVIDIA
2025-03-01
Average performance across 1 common benchmarks
Llama-3.3 Nemotron Super 49B
Qwen2.5-Coder 32B Instruct
Performance comparison across key benchmark categories
Llama-3.3 Nemotron Super 49B
Qwen2.5-Coder 32B Instruct
Available providers and their performance metrics
Llama-3.3 Nemotron Super 49B
Qwen2.5-Coder 32B Instruct
Llama-3.3 Nemotron Super 49B
Qwen2.5-Coder 32B Instruct