An individual has published the first performance benchmarks for a small LLM, Qwen3-0.6B, running on the Qualcomm QCS6490 chip. The process involved overcoming several technical hurdles, including issues with the export script and compiler rejections, before successfully compiling and profiling the model directly via API. The results show Qwen3-0.6B achieving 1,555 tokens/second for prefill and 24.6 tokens/second for decoding on the QCS6490, providing a crucial data point for this industrial-grade chip. AI
IMPACT Provides crucial performance data for LLMs on industrial-grade Qualcomm chips, enabling better hardware selection and optimization.
RANK_REASON Publication of performance benchmarks for a specific LLM on a particular hardware chip. [lever_c_demoted from research: ic=1 ai=0.7]
- Aimetti
- Dragonwing RB3 Gen 2
- llama.cpp
- ONNX
- QCS6490
- QNN
- Qualcomm
- Qwen3 0.6B
- Samsung Galaxy S25 series
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