Can I Run GLM-5 on a Apple M5 Ultra (256GB)?
Yes
Runs at Q8_0 — near-lossless quality.
Model size
230B
GPU memory
256GB
Smallest quant
Q4_K_M
Best fit
Q8_0
4 quantizations fit your 256GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 245.4 GB | 246.9 GB | 244.4 GB | +10.6 GB |
| Q6_K | 190.5 GB | 192.0 GB | 189.5 GB | +65.5 GB |
| Q5_K_M | 164.3 GB | 165.8 GB | 163.3 GB | +91.7 GB |
| Q4_K_M | 140.4 GB | 141.9 GB | 139.4 GB | +115.6 GB |
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Full model details
GLM-5 →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
Apple M5 Ultra (256GB) →
Top-ranked open-source models that fit in 256GB.
FAQ
Can the Apple M5 Ultra (256GB) run GLM-5?
Yes. The Apple M5 Ultra (256GB)'s 256GB of unified memory is enough to run GLM-5 at Q8_0 quantization (245.4GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 256GB. It uses about 245.4GB of memory and 246.9GB 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.