System · laptop
MacBook Pro M4 Max 128 GB
Runs models up to ~160B parameters at 4-bit in unified memory. Laptop with 128 GB unified memory.
- Unified memory
- 128 GB
- System RAM
- Shared
- Runs
- 18 of 19model variants, 8K
- Estimated cost
- ~$5,400
What it runs
Largest models that fit without spilling into system memory, at an 8K contextHow much text the model can consider at once, counted in tokens — roughly ¾ of a word each..
- VariantLlama 3.1 70B Instruct70.6B · Q4_K_M via llama.cppRuns well~8 tok/s est.
- VariantLlama 3.3 70B Instruct70.6B · Q4_K_M via llama.cppRuns well~8 tok/s est.
- VariantMixtral 8x7B Instruct v0.146.7B · Q4_K_M via llama.cppRuns well~42 tok/s est.
- VariantQwen2.5 32B Instruct32.8B · Q5_K_M via llama.cppRuns well~15 tok/s est.
- VariantQwen2.5-Coder 32B Instruct32.8B · Q8_0 via llama.cppRuns well~10 tok/s est.
- VariantDeepSeek-R1-Distill-Qwen-32B32.8B · Q4_K_M via llama.cppRuns well~17 tok/s est.
- VariantQwen3 30B-A3B30.5B · Q8_0 via llama.cppRuns well~88 tok/s est.
- VariantGemma 3 27B IT27.4B · Q4_K_M via llama.cppRuns well~21 tok/s est.
- VariantGemma 2 27B IT27.2B · Q4_K_M via llama.cppRuns well~21 tok/s est.
- VariantMistral Small 24B Instruct 250123.6B · Q6_K via llama.cppRuns well~18 tok/s est.
Components
Measured performance
| Model · quantization | Runtime | Context | Measurements | Source |
|---|---|---|---|---|
| Llama 3.3 70B Instruct MLX 4-bit (MLX Community) | MLX-LMmetal · 0.21.0 | 4K | 11.2 tok/s · Generation throughput 41 GB · Peak memory 110 tok/s · Prompt throughput 4,200 ms · Time to first token | Mutinai illustrative fixtures |
Community results
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Reviews
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