text model · Muse · macOS

Can I run Muse Glimmer 30B on Apple M4 Pro (24GB)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Muse Glimmer 30B needs ~18.2 GB even at Q4_K_M, but Apple M4 Pro (24GB) only has ~16 GB usable.

Needs ~18.2 GB Device usable ~16 GB

Needs ~18.2 GB even at Q4_K_M, but only ~16 GB is usable.

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

The gap is about 2.2 GB: Muse Glimmer 30B needs roughly 18.2 GB at Q4_K_M and Apple M4 Pro (24GB) leaves only about 16 GB usable for a model. The lightest tracked hardware that runs Muse Glimmer 30B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Muse Glimmer 30B on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed: ~18.2 GB
Usable on device: ~16 GB
Device memory: 24 GB

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Which quant fits

Quant ladder vs ~16 GB usable

Q2_K

~14.7 GB

Q3_K_M

~16.8 GB

Q4_K_M

~18.2 GB

Q5_K_M

~23.5 GB

Q6_K

~26.7 GB

Q8_0

~32.2 GB

FP16

~62.1 GB

The line marks Apple M4 Pro (24GB)'s ~16 GB budget; rungs past it are too large.

Model Muse

Parameters: 30B
Q4_K_M size: 16.12 GB
Q8_0 size: 30.12 GB
Context: 128k
Ollama tag: muse-glimmer:30b

Full Muse Glimmer 30B requirements →

Device macOS

Memory: 24 GB unified
Usable for weights: ~16 GB
Power draw: ~140 W
Best runtime: Ollama (MLX backend, preview) / MLX direct

Best models for Apple M4 Pro (24GB) →

What you can run instead

Run Muse Glimmer 30B 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 M4 Pro (24GB) run Muse Glimmer 30B?

No. Muse Glimmer 30B needs ~18.2 GB even at Q4_K_M, but Apple M4 Pro (24GB) only has ~16 GB usable.

How much memory does Muse Glimmer 30B need?

Apple M4 Pro (24GB) does not have enough memory. At Q4_K_M the weights are ~16.12 GB; with KV cache and runtime overhead, budget ~18.2 GB at a 4k context.

What is the best tool to run Muse Glimmer 30B 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

[![Muse Glimmer 30B on Apple M4 Pro (24GB)](https://localmodel.run/badge/muse-glimmer-30b/apple-m4-pro-24gb.svg)](https://localmodel.run/can-i-run/muse-glimmer-30b/apple-m4-pro-24gb)

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.