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text model · GLM · macOS

Can I run GLM-4.5-Air on Apple M3 Pro (18GB)?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. GLM-4.5-Air needs ~71.8 GB even at Q4_K_M, but Apple M3 Pro (18GB) only has ~12 GB usable.

Needs ~71.8 GB Device usable ~12 GB

Needs ~71.8 GB even at Q4_K_M, but only ~12 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 59.8 GB: GLM-4.5-Air needs roughly 71.8 GB at Q4_K_M and Apple M3 Pro (18GB) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs GLM-4.5-Air is the Apple M4 Max (128GB) at 128 GB. See GLM-4.5-Air on Apple M4 Max (128GB).

Q4_K_M needed
~71.8 GB
Usable on device
~12 GB
Device memory
18 GB
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Which quant fits

Quant ladder vs ~12 GB usable
Q2_K
~47.7 GB
Q3_K_M
~55.1 GB
Q4_K_M
~71.8 GB
Q5_K_M
~78.8 GB
Q6_K
~90.2 GB
Q8_0
~112.7 GB
FP16
~215.3 GB
The line marks Apple M3 Pro (18GB)'s ~12 GB budget; rungs past it are too large.

How to run it

On macOS use LM Studio (Polished GUI, ships MLX on Apple Silicon, one-click model downloads.).

Model GLM
Parameters
106B (MoE, 12B active)
Q4_K_M size
68.45 GB
Q8_0 size
109.39 GB
Context
128k
Full GLM-4.5-Air requirements →
Device macOS
Memory
18 GB unified
Usable for weights
~12 GB
Power draw
~70 W
Best runtime
Ollama (llama.cpp Metal backend) / MLX
Best models for Apple M3 Pro (18GB) →

What you can run instead

Run GLM-4.5-Air on other hardware

FAQ

Can Apple M3 Pro (18GB) run GLM-4.5-Air?

No. GLM-4.5-Air needs ~71.8 GB even at Q4_K_M, but Apple M3 Pro (18GB) only has ~12 GB usable.

How much memory does GLM-4.5-Air need?

Apple M3 Pro (18GB) does not have enough memory. At Q4_K_M the weights are ~68.45 GB; with KV cache and runtime overhead, budget ~71.8 GB at a 4k context. It is a Mixture-of-Experts model (106B total / 12B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run GLM-4.5-Air on macOS?

LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.

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Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.