Can I Run diffusiongemma 26B A4B it on a Apple M2 (24GB)?
Runs comfortably at Q6_K — minimal quality loss.
3 quantizations fit your 24.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 22.3 GB | 23.8 GB | 22.6 GB | +1.8 GB |
| Q5_K_M | 19.3 GB | 20.8 GB | 19.1 GB | +4.7 GB |
| Q4_K_M | 16.6 GB | 18.1 GB | 16.8 GB | +7.4 GB |
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Top-ranked open-source models that fit in 24.0GB.
FAQ
Can the Apple M2 (24GB) run diffusiongemma 26B A4B it?
Yes. The Apple M2 (24GB)'s 24.0GB of unified memory is enough to run diffusiongemma 26B A4B it at Q6_K quantization (22.3GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 24.0GB. It uses about 22.3GB of memory and 23.8GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.