MacBook M5 Pro and Qwen3.5 = Local AI Security System
sharpai.org
March 20, 2026
3 min read
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56/100
Summary
Qwen3.5-9B achieves a score of 93.8%, closely trailing GPT-5.4, while operating entirely on a MacBook Pro M5 at 25 tok/s and 765ms TTFT, using 13.8 GB of unified memory. The benchmark evaluates 96 tests across 15 suites focusing on tool use, security classification, and event deduplication, with zero API costs and full data privacy.
Key Takeaways
- Qwen3.5-9B running locally on a MacBook Pro M5 scores 93.8%, only 4.1 points behind GPT-5.4, with zero API costs and complete data privacy.
- The Qwen3.5-35B-MoE has a lower Time to First Token (TTFT) of 435ms compared to 508ms for GPT-5.4-nano.
- HomeSec-Bench evaluates LLMs on specific home security assistant workflows, focusing on tasks like reasoning, triage, and tool use.
- The benchmark suite includes 96 tests across 15 evaluation suites, assessing various capabilities such as security classification and multi-turn reasoning.
Community Sentiment
Positives
- The concept of a family-oriented AI server as a major purchase reflects a growing trend towards integrating AI into everyday life, enhancing home security and personal convenience.
- The idea of a context-based home security system could significantly reduce false alerts, making home monitoring more efficient and user-friendly.
Concerns
- The current barrier to entry for local AI models remains high at $2500, which limits accessibility for many potential users and families.
- Recent Qwen models are reportedly slower than their predecessors and other open weight models, raising concerns about their competitiveness in the market.
- The benchmarks for home security workflows appear simplistic, suggesting that the capabilities may not be as advanced as presented, which could mislead consumers.
