Can I run GLM 4.5 Air (MoE) locally?
GLM 4.5 Air (MoE) has 110.47 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 71.7 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2025-07-20. It's a mixture-of-experts model: all weights must fit in memory, but it generates faster than a dense model of the same size.
Memory needed by quantization
| Quant | Weights | Total needed (est.) |
|---|---|---|
| IQ1_S | 21.5 GB | 24.0 GB |
| IQ2_XXS | 28.4 GB | 31.2 GB |
| IQ2_M | 37.3 GB | 40.5 GB |
| Q2_K | 43.8 GB | 47.3 GB |
| IQ3_XXS | 42.3 GB | 45.7 GB |
| Q3_K_S | 50.4 GB | 54.3 GB |
| IQ3_M | 50.5 GB | 54.4 GB |
| Q3_K_M | 55.2 GB | 59.4 GB |
| IQ4_XS | 58.7 GB | 63.0 GB |
| Q4_0 | 62.1 GB | 66.6 GB |
| Q4_K_M | 67.0 GB | 71.7 GB |
| MXFP4 | 63.9 GB | 68.5 GB |
| Q5_K_M | 78.6 GB | 83.9 GB |
| Q6_K | 90.6 GB | 96.5 GB |
| Q8_0 | 117.4 GB | 124.6 GB |
| F16 | 220.9 GB | 233.4 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 0.77 GB | 0.41 GB | 0.22 GB |
| 8k | 1.54 GB | 0.82 GB | 0.43 GB |
| 16k | 3.09 GB | 1.64 GB | 0.87 GB |
| 32k | 6.17 GB | 3.28 GB | 1.74 GB |
| 64k | 12.35 GB | 6.56 GB | 3.47 GB |
| 128k | 24.70 GB | 13.12 GB | 6.95 GB |
From config.json: 46 KV-caching attention layers, 8 KV heads × 128 head dim. Max context 128k. The tables above assume 4k context.
Which GPUs and Macs can run it?
✅ fits · ⚠️ fits with little headroom · ❌ doesn't fit on this one device (multiple GPUs or RAM offload may work; check your setup). Apple Silicon assumes macOS lets the GPU use ~67–75% of unified memory. All fit verdicts are estimates.
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