MacBook Pro M5 Max · 64 GB
A portable Apple-native tier for larger quantized models. Sustained inference still depends on thermals, runtime support, and context length.
Sumber primerQwen3.8 Flash Next REAP-288
The highest listed result may be a tight or offloaded fit. For daily use, prefer the first result marked Lega and keep context modest.
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. The bundled mlx_lm.server is an OpenAI-compatible HTTP endpoint (default 127.0.0.1:8080), but upstream warns it implements only basic security checks and is not recommended for production.
Buka panduanModel open-weight perwakilan
Qwen3.8 Flash Next REAP-288
- Estimasi memori
- ~40.57 GB
- Konteks
- 7.6K recommended on measured 48 GB Mac
Llama 3.1 70B
- Estimasi memori
- ~46 GB
- Konteks
- 128K
Qwen3.6 35B-A3B
- Estimasi memori
- ~25 GB
- Konteks
- 262K native
Qwen3 32B
- Estimasi memori
- ~24.5 GB
- Konteks
- 32K+
Qwen3 30B-A3B
- Estimasi memori
- ~22.5 GB
- Konteks
- 32K+
Qwen3.6 27B
- Estimasi memori
- ~18.5 GB
- Konteks
- 262K native
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: Qwen3.8 Flash Next REAP-288 (Ketat), Llama 3.1 70B (Ketat), Qwen3.6 35B-A3B (Lega), Qwen3 32B (Lega), Qwen3 30B-A3B (Lega), Qwen3.6 27B (Lega).