Tiny LLM Benchmark: Jetson Orin Nano Super 8GB
The article benchmarks non-reasoning Tiny LLMs (small language models) on the Jetson Orin Nano Super 8GB. It evaluates models like Phi-3, Gemma, and Llama variants on this edge device, measuring performance metrics such as tokens per second.
Background
- The Jetson Orin Nano Super 8GB is NVIDIA's $250 edge AI computer, built to run ML models locally without cloud dependency. Popular among hobbyists, students, and robotics developers.
- "Non-reasoning" means standard LLMs that generate answers directly, unlike "reasoning" models (OpenAI o1, DeepSeek-R1) that internally deliberate step-by-step before answering.
- The post benchmarks tiny open-weight LLMs (1B–8B parameters) on this device. Key models: Meta's Llama 3.2 (1B/3B), Microsoft Phi-3, Mistral TinyLlama.
- Results show usable speeds (10–50 tokens/sec) on $250 hardware — practical local AI without expensive cloud GPUs.