Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
NVIDIA
Llama-3.1-Nemotron-Ultra-253B-v1 is a 253-billion-parameter model from NVIDIA, derived from Meta's Llama 3.1 405B using neural architecture search (NAS) compression combined with NVIDIA's Nemotron post-training pipeline, which recovers and exceeds the base model's capability after structural compression. Released in April 2025, it supports toggling between a standard instruction mode and an extended reasoning mode via system prompt, allowing the same model to handle both rapid responses and deliberate chain-of-thought tasks. It is the flagship of the Nemotron family, available open-weight on HuggingFace and through NVIDIA NIM for enterprise inference.
Alibaba / Qwen
Qwen2.5-32B-Instruct is a 32-billion-parameter open-weight model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 series trained on 18 trillion tokens. The model is positioned as a high-capability option for developers with access to multi-GPU setups or high-VRAM hardware, offering strong performance on coding, structured reasoning, and multilingual tasks while remaining fully open under Apache 2.0. Its 128K context window and support for structured output generation made it a popular choice for document processing and agentic workflows in the open-source community.
6 months newer
Qwen2.5 32B Instruct
Alibaba / Qwen
2024-09-19

Llama-3.1 Nemotron Ultra 253B
NVIDIA
2025-04-07
Available providers and their performance metrics
Llama-3.1 Nemotron Ultra 253B
Qwen2.5 32B Instruct
Llama-3.1 Nemotron Ultra 253B
Qwen2.5 32B Instruct