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
Qwen2.5-7B-Instruct is a 7-billion-parameter open-weight language model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 series trained on 18 trillion tokens with improved code, math, and multilingual coverage. The model delivers significantly stronger instruction-following, structured output generation, and long-context handling compared to its predecessor, supporting 128K context windows in a compact form factor. It became widely adopted as a foundation for fine-tuning, RAG pipelines, and on-device deployment due to its balance of capability and efficiency.
6 months newer
Qwen2.5 7B 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 7B Instruct
Llama-3.1 Nemotron Ultra 253B
Qwen2.5 7B Instruct