Comprehensive side-by-side LLM comparison
. 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
Qwen3-Max, released by Alibaba in September 2025 as an API preview, is a large language model exceeding one trillion parameters built for complex reasoning and long-context tasks. It features a 262K token context window, hybrid thinking modes that allow switching between direct generation and extended chain-of-thought, and is available as a proprietary cloud API via Alibaba Cloud and Qwen Chat. Qwen3-Max targets demanding reasoning, multilingual analysis, and applications requiring frontier-level performance from the Qwen3 generation.
8 months newer

Llama 3.1 Nemotron Nano 8B
NVIDIA
2025-01-06
Qwen3-Max
Alibaba / Qwen
2025-09-05
Context window and performance specifications
Available providers and their performance metrics
Llama 3.1 Nemotron Nano 8B
Qwen3-Max
OpenRouter
Llama 3.1 Nemotron Nano 8B
Qwen3-Max
Llama 3.1 Nemotron Nano 8B
Qwen3-Max