Benchmarking Local LLMs on a £300 Snapdragon Mini PC: 35B at 30 tokens/s, 80B Surpassing RAM Limits

Summary:A Reddit user conducted detailed benchmarks of a £300 Snapdragon Mini PC (Snapdragon X1-26-100, 32GB RAM) running local Large Language Models (LLMs), including Qwen3.6 35B and Qwen3-Next 80B. The results demonstrated that the 35B model achieved approximately 30 tokens/s in generation speed using CPU, while the 80B model, despite exceeding RAM capacity, managed 17-18 tokens/s through streaming. The tests also explored the impact of different quantization formats and caching optimizations, highlig

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Benchmarking Local LLMs on a £300 Snapdragon Mini PC

Background and Motivation

A Reddit user purchased a £300 Lenovo IdeaCentre Mini (Snapdragon X1-26-100, 32GB RAM, CPU-only) to test software compatibility with ARM-based Windows. Impressed by its affordability, they decided to explore its potential for running local Large Language Models (LLMs).

Test Environment and Configuration

• Hardware: Snapdragon X1-26-100 CPU, 32GB LPDDR5 RAM, Adreno X1-45 GPU (currently not useful for LLMs), NPU unused.
• Software: Used llama.cpp and a re-coded version of Janas (an MoE expert caching tool for ARM).
• Models: Qwen3.6 35B A3B (quantized as Q4_0), Qwen3-Next 80B A3B, Gemma 26B.

Results

1. Qwen3.6 35B A3B:

   • Read Speed: ~118 tokens/s
   • Write Speed: 24.5 tokens/s
   • MTP (Multi-Threading Processing): 29-33 tokens/s

2. Qwen3-Next 80B A3B:

   • Write Speed: 17-18 tokens/s (MTP)

3. Gemma 26B:

   • Read Speed: 134 tokens/s
   • Write Speed: 29.5 tokens/s
   • MTP: Not yet tested

Optimizations and Improvements

To overcome RAM limitations, the user experimented with Janas, which caches MoE experts in RAM and streams the rest from NVMe. Since Janas is x86-only, they re-coded it for ARM, including NEON kernels for each quantization format and testing i8mm.

• Janas Optimized Performance:
  • Qwen3.6 35B A3B: Read speed ~60 tokens/s, write speed 17.2 tokens/s, MTP 29-31 tokens/s
  • Gemma 26B: Read speed 115 tokens/s, write speed 23.5 tokens/s, MTP 32-34 tokens/s
  • 80B Model: Read speed TBC, write speed 9.8 tokens/s, MTP 17-18 tokens/s

Additionally, the user compressed the expert cache to 12GB and found the write speed remained at 24 tokens/s, indicating that even a 16GB Snapdragon device could run the 35B-A3B model.

Conclusion and Outlook

The mini PC demonstrated surprising performance with no GPU and only ~35W power consumption. The user also attempted to connect two devices via USB4 for distributed computing and successfully ran a 122B Qwen model. Overall, the device showcases the potential of ARM architecture for local LLM deployment, particularly in budget and power-sensitive scenarios.

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Source: Reddit r/LocalLLaMA (2026-10-15)

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Tags: #Snapdragon Follow #Local LLM Follow #ARM Architecture Follow #Qwen Models Follow #Multi-Threading Follow