Can I Run Gemma 4 26B A4B (free) on a Apple M5 (24GB)?
Runs comfortably at Q6_K — minimal quality loss.
6 quantizations fit your 24.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q6_KBEST | 22.8 GB | 24.3 GB | 23.2 GB | +1.2 GB |
| Q5_K_M | 19.8 GB | 21.3 GB | 21.1 GB | +4.2 GB |
| Q5_K_S | 19.3 GB | 20.8 GB | 18.9 GB | +4.7 GB |
| Q4_K_M | 17.1 GB | 18.6 GB | 16.9 GB | +6.9 GB |
| Q4_K_S | 16.2 GB | 17.7 GB | 16.5 GB | +7.8 GB |
| Q3_K_M | 12.1 GB | 13.6 GB | 12.7 GB | +11.9 GB |
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All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 24.0GB.
FAQ
Can the Apple M5 (24GB) run Gemma 4 26B A4B (free)?
Yes. The Apple M5 (24GB)'s 24.0GB of unified memory is enough to run Gemma 4 26B A4B (free) at Q6_K quantization (22.8GB required).
What's the best quantization to use?
Q6_K is the highest-precision quantization that fits in your 24.0GB. It uses about 22.8GB of memory and 24.3GB 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.