The MacBook M2 Pro 16GB has 16 GB of unified memory and 200 GB/s of memory bandwidth, which is what mostly decides generation speed. Below is the expected speed for each model at the best quantization that fits.
| Model | Quantization | Memory | Generation | First token |
|---|---|---|---|---|
| Qwen 3.6/3.8 27B | Q4_K_M | Doesn't fit | Won't run | — |
| GLM-5.3 Flash | UD-IQ1_S | Doesn't fit | Won't run | — |
| GPT-OSS 20B | MXFP4 | Doesn't fit | Won't run | — |
| Gemma 4 26B A4B | Q4_K_M | Doesn't fit | Won't run | — |
| Qwen 3.5/3.6 35B A3B | Q4_K_M | Doesn't fit | Won't run | — |
| Ornith 1.5 35B A3B | Q4_K_M | Doesn't fit | Won't run | — |
| DeepSeek V4 Flash | UD-IQ1_S | Doesn't fit | Won't run | — |
| GPT-OSS 120B | MXFP4 | Doesn't fit | Won't run | — |
| Gemma 4 31B | Q4_K_M | Doesn't fit | Won't run | — |
| Llama 3.1 8B | Q4_K_M | Fits | 24 tok/s | 0.5 s |
| Qwen 3.5 9B | Q4_K_M | Fits | 17 tok/s | 0.5 s |
| DeepSeek R1 Distill 14B | Q4_K_M | Fits | 13 tok/s | 0.6 s |
| Ornith 1.5 9B | Q4_K_M | Fits | 16 tok/s | 0.5 s |
| Muse Glimmer 30B | Q4_K_M | Doesn't fit | Won't run | — |
| Qwen3 30B A3B | Q4_K_M | Doesn't fit | Won't run | — |
Estimates for a short prompt on a single device. Measured numbers come from community benchmarks (r/LocalLLaMA, localscore.ai and more); others are derived from similar setups or projected from specs. Open source on GitHub.