Qwen3.5 Small tests starter Mac limits

The core story is practical: on a 16GB MacBook Air, the winning model is the one that fits comfortably, not the one with the biggest parameter count on paper.

• –9B-class quantized models are the sensible baseline here; 15B can be workable in some setups, but context length and headroom get tight fast
• –Unified memory is the real constraint, so quantization level, context size, and inference backend matter as much as raw model size
• –The “truly uncensored” framing is common in local-LLM circles, but the tradeoff is usually alignment versus usability rather than some perfect open model
• –Qwen3.5 Small is a reasonable benchmark for this class of machine because it sits in the sweet spot between capability and footprint
• –The most useful follow-up for readers would be a simple Mac optimization checklist plus direct comparisons against similarly sized open-weights models