Comprehensive side-by-side LLM comparison
Qwen2.5-Coder 32B Instruct leads with 5.6% higher average benchmark score. Overall, Qwen2.5-Coder 32B Instruct is the stronger choice for coding tasks.
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-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.
1 month newer
Qwen2.5-Coder 32B 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 32B Instruct
Performance comparison across key benchmark categories
Llama 3.1 Nemotron Nano 8B
Qwen2.5-Coder 32B Instruct
Available providers and their performance metrics
Llama 3.1 Nemotron Nano 8B
Qwen2.5-Coder 32B Instruct
Llama 3.1 Nemotron Nano 8B
Qwen2.5-Coder 32B Instruct