Google Gemma 2B speed on Apple M2 Max and quantization-level VRAM fit.
Apple M2 Max meets the minimum VRAM requirement for Q4 inference of Google Gemma 2B. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
Apple M2 Max can run Google Gemma 2B with Q4 quantization. At approximately 64 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 94GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 2GB | 96GB | 64.41 tok/s | ✅ Fits comfortably |
| Q8 | 3GB | 96GB | 45.09 tok/s | ✅ Fits comfortably |
| FP16 | 6GB | 96GB | 24.48 tok/s | ✅ Fits comfortably |
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Apple M2 Max can run Google Gemma 2B at Q4 with an estimated 64 tok/s.
Q4 inference is estimated to need about 2GB VRAM on this page, while Apple M2 Max has 96GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.