Can I Run GLM-4.5 on a AMD Instinct MI325X?
Yes
Runs at Q5_K_M — good quality with reasonable headroom.
Model size
358B
GPU memory
256GB
Smallest quant
Q2_K
Best fit
Q5_K_M
10 quantizations fit your 256GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q5_K_MBEST | 255.4 GB | 256.9 GB | 21.3 GB | +0.6 GB |
| Q5_K_S | 248.2 GB | 249.7 GB | 75.7 GB | +7.8 GB |
| Q4_1 | 224.9 GB | 226.4 GB | 67.0 GB | +31.1 GB |
| Q4_K_M | 218.2 GB | 219.7 GB | 18.1 GB | +37.8 GB |
| Q4_K_S | 206.1 GB | 207.6 GB | 64.7 GB | +49.9 GB |
| Q4_0 | 202.5 GB | 204.0 GB | 60.5 GB | +53.5 GB |
| Q3_K_L | 160.4 GB | 161.9 GB | 57.6 GB | +95.6 GB |
| Q3_K_M | 151.0 GB | 152.5 GB | 14.4 GB | +105.0 GB |
| Q3_K_S | 138.9 GB | 140.4 GB | 13.0 GB | +117.1 GB |
| Q2_K | 118.8 GB | 120.3 GB | 45.3 GB | +137.2 GB |
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Full model details
GLM-4.5 →
All quant variants, benchmark scores, and use-case tags.
Best models for this GPU
AMD Instinct MI325X →
Top-ranked open-source models that fit in 256GB.
FAQ
Can the AMD Instinct MI325X run GLM-4.5?
Yes. The AMD Instinct MI325X's 256GB of VRAM is enough to run GLM-4.5 at Q5_K_M quantization (255.4GB required).
What's the best quantization to use?
Q5_K_M is the highest-precision quantization that fits in your 256GB. It uses about 255.4GB of memory and 256.9GB 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.