Comprehensive side-by-side LLM comparison
Llama 3.1 Nemotron Nano 8B leads with 1.1% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
NVIDIA
Llama-3.1-Nemotron-Nano-8B-v1 is an 8-billion-parameter model from NVIDIA, developed as a fine-tuned variant of Meta's Llama 3.1 8B using NVIDIA's Nemotron post-training methodology, which applies reinforcement learning and process reward modeling to enhance instruction-following and reasoning capability over the base model. The Nano designation marks it as the entry-level member of the Nemotron family, optimized for efficient inference on a single GPU while delivering meaningfully improved performance on instruction alignment and agentic tasks compared to standard Llama 3.1. Released open-weight on HuggingFace, it is designed for deployment in NVIDIA-accelerated environments and supports NVIDIA NIM for enterprise inference.
Alibaba / Qwen
Qwen2.5-Coder-7B-Instruct is a 7-billion-parameter code-specialized model from Alibaba, released in November 2024 as part of the Qwen2.5-Coder family, trained on a curated corpus spanning 92 programming languages with emphasis on code generation, debugging, and fill-in-the-middle completion. Built on the Qwen2.5 architecture, it extends the base series' improvements in instruction-following and long-context handling to coding-specific tasks within a compact deployable footprint. It became popular for integration into IDE extensions, CI pipelines, and self-hosted code assistant tools.
1 month newer
Qwen2.5-Coder 7B Instruct
Alibaba / Qwen
2024-11-12

Llama 3.1 Nemotron Nano 8B
NVIDIA
2025-01-06
Average performance across 1 common benchmarks
Llama 3.1 Nemotron Nano 8B
Qwen2.5-Coder 7B Instruct
Performance comparison across key benchmark categories
Llama 3.1 Nemotron Nano 8B
Qwen2.5-Coder 7B Instruct
Available providers and their performance metrics
Llama 3.1 Nemotron Nano 8B
Qwen2.5-Coder 7B Instruct
Llama 3.1 Nemotron Nano 8B
Qwen2.5-Coder 7B Instruct