text model · GLM · macOS

Can I run GLM-4.7-Flash on Apple M5 Max (128GB)?

Compatibility verdict VRAM threshold engine

Yes, it runs GPU accelerated

Yes. GLM-4.7-Flash runs on Apple M5 Max (128GB) at Q4_K_M (~19.2 GB of ~96 GB usable).

Needs ~19.2 GB Device usable ~96 GB

Runs at Q4_K_M using ~19.2 GB of ~96 GB usable. You have room for FP16 for higher quality.

That figure is at a 4k context and moves about ±15% as context length changes. Apple M5 Max (128GB) leaves ~76.8 GB of headroom, room to step up to FP16 for higher quality.

Q4_K_M needed: ~19.2 GB
Usable on device: ~96 GB
Device memory: 128 GB
Best quant: Q4_K_M

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Which quant fits

Quant ladder vs ~96 GB usable

Q2_K

~14.7 GB

Q3_K_M

~16.8 GB

Q4_K_M

~19.2 GB

Q5_K_M

~23.5 GB

Q6_K

~26.7 GB

Q8_0

~31.8 GB

FP16

~57.9 GB

The line marks Apple M5 Max (128GB)'s ~96 GB budget; rungs past it are too large.

Run it

Install commands macOS

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama

$ ollama run glm-4.7-flash:latest

llama.cpp

$ llama-cli -hf unsloth/GLM-4.7-Flash-GGUF:Q4_K_M

LM Studio

$ lms get unsloth/GLM-4.7-Flash-GGUF

Model GLM

Parameters: 30B (MoE, 3B active)
Q4_K_M size: 17.05 GB
Q8_0 size: 29.66 GB
Context: 200k
Ollama tag: glm-4.7-flash:latest

Full GLM-4.7-Flash requirements →

Device macOS

Memory: 128 GB unified
Usable for weights: ~96 GB
Best runtime: MLX direct / Ollama (MLX backend)

Best models for Apple M5 Max (128GB) →

You could also run

Run GLM-4.7-Flash on other hardware

Nvidia GeForce RTX 4090 (24GB)Nvidia GeForce RTX 3090 (24GB)AMD Radeon RX 7900 XTX (24GB)Nvidia GeForce RTX 5090 (32GB)32GB RAM Laptop (CPU/iGPU only)Apple M5 (32GB)

FAQ

Can Apple M5 Max (128GB) run GLM-4.7-Flash?

Yes. GLM-4.7-Flash runs on Apple M5 Max (128GB) at Q4_K_M (~19.2 GB of ~96 GB usable).

How much memory does GLM-4.7-Flash need?

Apple M5 Max (128GB) has room to spare. At Q4_K_M the weights are ~17.05 GB; with KV cache and runtime overhead, budget ~19.2 GB at a 4k context. It is a Mixture-of-Experts model (30B total / 3B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run GLM-4.7-Flash 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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Markdown

[![GLM-4.7-Flash on Apple M5 Max (128GB)](https://localmodel.run/badge/glm-4.7-flash/apple-m5-max-128gb.svg)](https://localmodel.run/can-i-run/glm-4.7-flash/apple-m5-max-128gb)

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.