LLM Showdown: Qwen, Nemotron, and Qwythos models tested on coding task

A local LLM showdown tested five models on a coding task, revealing significant infrastructure challenges and varied performance. The author encountered and patched two critical bugs in the llama.cpp tool-call parser, affecting Qwythos-9B and Nemotron-3-Nano. Despite these issues and the models' own failures, the tests provided insights into dense versus Mixture-of-Experts (MoE) architectures, with Qwen 3.6 models and Nemotron-3-Nano being key contenders. AI

IMPACT Highlights performance differences and infrastructure issues in running local LLMs, informing hardware and software choices for AI operators.

RANK_REASON The item details a comparative benchmark of multiple LLMs on a specific task, including infrastructure challenges encountered during testing. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

• AMD
• GLM 4.7 Flash
• llama.cpp
• Nemotron 3 Nano
• NVIDIA
• Nvidia Rtx 5090
• playwright
• Qwen-3.6 27B
• Qwen 3.6-35B-A3B
• Qwythos-9B
• Ryzen 9 9950X3D
• Ubuntu

• model release

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