Apple M5 Pro (24GB)
The Apple M5 Pro (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 307 GB/s unified memory bandwidth.
Memory
24 GB
Usable Memory Ceiling
18 GB (75% max allocated to GPU)
Bandwidth
307 GB/s
Max Inference Class
14B Models (Q4)
TDP
95W
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:
Need custom layer dimensions, offloading configurations, or distributed multi-node topology?
Open in Advanced VRAM CalculatorInference Feasibility
Maximum model parameter class runnable by weight precision.
Context:
4-bit
14B Models
8-bit
14B Models
16-bit
8B Models
Fine-Tuning Feasibility
Hardware capacity for local training and adapter fine-tuning.
Context Length:
QLoRA
14B Models
LoRA
8B Models
Full Parameter Training
1B Models
Workload Recommendations
Guidance for optimal precision and operational ceilings on Apple M5 Pro (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 307 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 68 tok/s on an 8B Q4 model and 8 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.