MacBook Pro M3 Pro 36GB Integrated memory 36GB · Usable space for model approximately 30GB
M3 generation laptop configuration that reliably powers 12B~14B dense and 26B MoE Q4 models with 150 GB/s integrated memory bandwidth and 36GB memory.
Hardware core specifications
- available memory
- 30GB
- Memory bandwidth
- 150GB/s
- Estimated sustained LLM load
- About 70W
- Korean price range (KRW)
- 280 × KRW 10,000–290 × KRW 10,000
a person who fits well
- Utilize 30GB of available memory
- Quiet finished product composition
- K2 Horizon MoVA 36B-A4B-level local inference
In this case skip it
Unified memory is advantageous for loading large models, but CUDA-specific tools and multi-GPU workflows should be explored separately.
Recommended format for each device 4K input
The model you will experience with this equipment
K2 Horizon 0.9B
Required 1.03GB · spare time
MLX 4-bit
Decode
198.1 ~ 220.8 tok/s
First token
1.4 to 3.3 seconds
K2 Horizon MoVA 36B-A4B
recommendedRequired 21.94GB · spare time
MLX 4-bit
Decode
44.5 ~ 49.6 tok/s
First token
8.1 to 20.5 seconds
Actual speed may vary depending on runtime version, cooling status, context length and quantization file.
On sales pages, look at memory before chips.
The model and speed assumptions above change if the product is not the 36GB configuration.
Frequently Asked Questions
- Which local LLM can be run on the MBP M3 Pro 36GB?
- You can compare K2 Horizon 0.9B, K2 Horizon MoVA 36B-A4B, etc. with 4K input and recommended formats. Memory requirements vary depending on model and context length.
- What is the local LLM computing power of the MBP M3 Pro 36GB?
- Expected to draw approximately 70W under sustained load, with an actual range estimated between 50–100W.
- Are the displayed token speeds ground truth?
- These ranges normalize collected benchmark measurements to the same conditions. Only combinations without matching measurements are estimated from nearby measured values. Results can vary by runtime, cooling, model file, and context length.
Equipment to compare together
similar memory
Mac mini M4 32GB
Consider this configuration if you want to run 27B Q4 without building a new PC. Moving up makes sense if 24GB was running out of memory. If the model and cache already fit, however, choosing 32GB does not make the chip itself faster.
similar memory
Mac mini M6 32GB
If you plan to run a Qwen 27B-class Q4 model while keeping a browser or document app open, the 32GB configuration belongs on the shortlist. It has the same 170GB/s memory bandwidth as the 24GB M6, so the reason to buy 8GB more is the headroom left after loading the model. It launched on September 22, 2026, and can now be compared using current configurations and prices.
similar memory
RTX 5090 32GB
Compare this card if you repeatedly generate images or run 27B–35B inference and want shorter waits. But 32GB is still a limit. Buying on compute performance alone, without checking the model, input and image resolution, may leave you offloading again.