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The Apple M4 (24GB) uses unified memory architecture. For local LLM inference, macOS allocates up to 75% (18 GB) of total system RAM for GPU model weights and KV cache, with 120 GB/s unified memory bandwidth.

Memory

24 GB

Usable Memory Ceiling

18 GB (75% max allocated to GPU)

Bandwidth

120 GB/s

Max Inference Class

14B Models (Q4)

TDP

45W

VRAM Usage vs Context Length

Simulated memory requirements as context increases. Curves crossing above the reference line will cause Out Of Memory (OOM) errors.

Precision:

Model Compatibility & Speed Matrix

Simulated inference throughput and memory feasibility across popular open-weights models.

Context:

KV Cache:

ModelParametersPrecisionTPS (Approx.)TTFTCan Run
Llama 3.2 1B

1.2B

INT4

191 tok/s

~297 ms

Llama 3.2 1B

1.2B

Q8

143 tok/s

~298 ms

Llama 3.2 1B

1.2B

FP16

92 tok/s

~302 ms

Llama 3.2 3B

3.2B

INT4

110 tok/s

~731 ms

Llama 3.2 3B

3.2B

Q8

73 tok/s

~736 ms

Llama 3.2 3B

3.2B

FP16

41 tok/s

~746 ms

Mistral 7B

7.2B

INT4

61 tok/s

~1573 ms

Mistral 7B

7.2B

Q8

37 tok/s

~1584 ms

Mistral 7B

7.2B

FP16

-

-

Llama 3.1 8B

8.0B

INT4

56 tok/s

~1742 ms

Llama 3.1 8B

8.0B

Q8

32 tok/s

~1905 ms

Llama 3.1 8B

8.0B

FP16

-

-

Mistral Nemo 12B

12.2B

INT4

39 tok/s

~2636 ms

Mistral Nemo 12B

12.2B

Q8

-

-

Mistral Nemo 12B

12.2B

FP16

-

-

Qwen 2.5 14B

14.7B

INT4

31 tok/s

~3436 ms

Qwen 2.5 14B

14.7B

Q8

-

-

Qwen 2.5 14B

14.7B

FP16

-

-

DeepSeek R1 32B

32.5B

INT4

-

-

DeepSeek R1 32B

32.5B

Q8

-

-

DeepSeek R1 32B

32.5B

FP16

-

-

Llama 3.3 70B

70.6B

INT4

-

-

Qwen 2.5 72B

72.7B

INT4

-

-

DeepSeek V3 671B

671B (37B active)

INT4

-

-

Need custom layer dimensions, offloading configurations, or distributed multi-node topology?

Open in Advanced VRAM Calculator

Inference Feasibility

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

14B Models

8-bit

Q8

14B Models

16-bit

FP16

8B Models

Fine-Tuning Feasibility

Hardware capacity for local training and adapter fine-tuning.

Context Length:

QLoRA

4-bit

14B Models

LoRA

16-bit

8B Models

Full Parameter Training

1B Models

Workload Recommendations

Guidance for optimal precision and operational ceilings on Apple M4 (24GB).

Inference Sweet Spot

Optimal for 8B models across extended context (32k+). 14B models fit comfortably at Q4 precision with standard context.

Bandwidth & Speed Profile

With 120 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 27 tok/s on an 8B Q4 model and 3 tok/s on a 70B Q4 model.

Unified Memory Headroom

macOS limits GPU memory allocation to approximately 75% of physical unified RAM by default to ensure system stability.