A user has successfully run large language models on a budget-friendly Lenovo IdeaCentre Mini PC equipped with a Snapdragon X1-26-100 processor and 32GB of RAM. Despite the lack of GPU acceleration, the system achieved impressive performance, running a 35B parameter coder model at approximately 30 tokens/second and an 80B model at 17-18 tokens/second using CPU-based inference with custom ARM optimizations. The user explored techniques like caching model experts in RAM and streaming from NVMe to overcome memory limitations, even experimenting with connecting two such PCs for larger model execution. AI
IMPACT Demonstrates the growing capability of consumer hardware for running large language models locally, potentially lowering barriers to entry for AI experimentation.
RANK_REASON User-level exploration of running LLMs on consumer hardware, not a frontier release or significant industry event.
- Gemma 26B
- janas
- Lenovo IdeaCentre Mini
- llama.cpp
- Qualcomm Snapdragon
- Qwen3.6 35B A3B
- Qwen3-Next 80B A3B
- Snapdragon X1-26-100
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