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Apple M4 (32GB)

The Apple M4 (32GB) has 32 GB VRAM and 120 GB/s memory bandwidth. It can run 43 of our 70 tracked models natively in VRAM at 8k context.

With 32 GB LPDDR5X, the Apple M4 (32GB) is a laptop-tier GPU that can run 43 models natively. It handles 70B-class models at Q4 quantization.

Apple M4 (32GB): Base M4 with 32GB LPDDR5X at 120 GB/s. 10-core CPU (4P+6E).

14B at Q4 native. 27B tight. ~6-10 t/s for 7B.

MLX and llama.cpp support. Entry-level Mac LLM option.

VendorApple
ArchitectureApple M4
CPU cores10 (4P + 6E)
VRAM32 GB (unified)
Memory typeLPDDR5X
Memory bandwidth120 GB/s
Compute backendMETAL
TierLaptop
Released2024
Models (native)43 / 70
Models (offload)0 / 70
Software: MLX gives the best performance on Apple Silicon; llama.cpp Metal backend is a solid alternative. Both are well-supported by Ollama.

Popular models for this GPU

Models this GPU runs natively in VRAM (43)

Too large for this GPU (27)

Frequently asked questions

How much VRAM does the Apple M4 (32GB) have?
The Apple M4 (32GB) has 32 GB of LPDDR5X with 120 GB/s memory bandwidth (unified system memory, shared between CPU and GPU).
What is the Apple M4 (32GB) best for?
With 32 GB of VRAM, the Apple M4 (32GB) is well-suited for running 7B–32B models at Q4 with room for context, making it a great all-rounder for local LLM inference.
What LLMs can the Apple M4 (32GB) run locally?
The Apple M4 (32GB) can run 43 of the 70 open-weight models tracked by CanItRun natively in VRAM at 8k context. Top options include: Llama 3.1 8B Instruct at BF16, Llama 3.2 3B Instruct at FP32, Llama 3.2 1B Instruct at FP32.
Can the Apple M4 (32GB) run Llama 3.3 70B Instruct?
The Apple M4 (32GB) does not have enough VRAM to run Llama 3.3 70B Instruct. You would need more VRAM or a lower quantization level.
Can the Apple M4 (32GB) run Qwen 3.6 27B?
Yes. The Apple M4 (32GB) runs Qwen 3.6 27B natively in VRAM at Q6_K quantization, achieving approximately 5.4 tokens per second.
Can the Apple M4 (32GB) run Llama 3.1 8B Instruct?
Yes. The Apple M4 (32GB) runs Llama 3.1 8B Instruct natively in VRAM at BF16 quantization, achieving approximately 7.5 tokens per second.