HARDWARE / UNIFIED MEMORY
Apple silicon · 32 GB
24B–32B Q4 models become practical for one local user.
M-series Pro / Max32 GB
01 / PRACTICAL CEILING
Qwen3 32B
The highest listed result may be a tight or offloaded fit. For daily use, prefer the first result marked Comfortable and keep context modest.
02 / DEFAULT RUNTIME
MLX LM
Native Apple silicon inference, experimentation and fine-tuning. Only for Apple silicon. Use an MLX-converted model and tune KV cache size for long contexts.
開啟指南03 / MODEL ENVELOPE
代表性開放權重模型
Alibaba Qwen
Qwen3 32B
32BGGUF Q4
- 估算記憶體
- ~24.5 GB
- 上下文
- 32K+
Alibaba Qwen
Qwen3 30B-A3B
30B3B active · GGUF Q4 MoE
- 估算記憶體
- ~22.5 GB
- 上下文
- 32K+
Google
Gemma 3 27B
27BINT4
- 估算記憶體
- ~20.5 GB
- 上下文
- 128K
Mistral AI
Devstral Small 2 24B
24BGGUF Q4 / BF16
- 估算記憶體
- ~18.5 GB
- 上下文
- 256K
OpenAI
gpt-oss-20b
21B3.6B active · MXFP4
- 估算記憶體
- ~16 GB
- 上下文
- 128K
Alibaba Qwen
Qwen3 14B
14BGGUF Q4
- 估算記憶體
- ~11.2 GB
- 上下文
- 32K+
注意
Fit is based on estimated total model memory. Driver support, KV cache, multimodal projectors, concurrency, and desktop applications can all reduce available headroom. Current fit: Qwen3 32B (Tight), Qwen3 30B-A3B (Tight), Gemma 3 27B (Tight), Devstral Small 2 24B (Tight), gpt-oss-20b (Comfortable), Qwen3 14B (Comfortable).