Mac mini M4 16GB If you are focusing on 8B to 12B, it is worth considering. For larger models, reserve more memory.
This is the right configuration to minimize costs and start with 8B to 12B models.
Speed and memory for the same model
Hardware core specifications
- Available memory
- 13GB
- Memory bandwidth
- 120GB/s
- Estimated sustained LLM load
- About 42W
- Korean price range (KRW)
- 165 × KRW 10,000–169 × KRW 10,000
Who it fits
- Summary, translation, light coding
- Quiet, always-on operation
- Private Local LLM
Skip it if
The available memory is small, making it difficult to use models larger than 20B and long contexts together.
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
154 ~ 172.1 tok/s
First token
1.5 to 3.8 seconds
Gemma 4 12B
recommendedRequired 8GB · titration
MLX 4-bit
Decode
11.6 ~ 12.9 tok/s
First token
12.8 ~ 31.1 s
Gemma 4 26B-A4B (MoE)
Required 15.55GB · tight
MLX 4-bit
Decode
9.6 ~ 15 tok/s
First token
6.2 ~ 18.0 s
Actual speed varies with runtime version, cooling, context length and quantization file.
purchase judgment
What tasks is it suitable for?
Document/Summary
SuitableFits short documents and 8B to 12B models.
Coding assistance
ConditionalSmall models are possible, but large storage contexts are tight.
Create image
ConditionalIt focuses on lightweight models and has fewer choices than the NVIDIA ecosystem.
- The first thing to get stuck
- The first limitation is the context length, as we need to fit the model and KV cache together in 13GB.
- Configuration to check
- M4 · Integrated memory 16GB · SSD 512GB or more
- Criteria for spending more money
- It is enough if you only use 8B~12B. If you are thinking of 27B, 24GB or more is better from the beginning.
On sales pages, look at memory before chips.
The model and speed assumptions above change if the product is not the 16GB configuration.
Frequently asked questions
- What LLM can be run on the Mac mini M4 16GB?
- K2 Horizon 0.9B, Gemma 4 12B, Gemma 4 26B-A4B (MoE) and others with a 4K input and the recommended format. Required memory varies by model and context length.
- What is the local LLM power of the Mac mini M4 16GB?
- Sustained load is about 42 W, with an actual range of 28–58 W.
- Are the displayed token speeds ground truth?
- This is a range aligned to collected benchmark measurements under the same conditions. Combinations without a matching measurement are estimated from the nearest result and vary with runtime, cooling, quantization file and context length.
Equipment to compare together
Memory headroom
Mac mini M4 24GB
If you summarize short documents and ask about small sections of code, first check whether the model you plan to use gives useful answers. If a 12B Q4 model does the job, 32GB is worth considering only when your work needs more memory headroom.
27B loading
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.
Generation
RTX 3090 24GB
If you own an RTX 3090, first check whether the target model and context fit in 24GB. Newer hardware alone is not a reason to replace a card that completes your work. For a used purchase, include power, cooling, case compatibility and return terms in the cost.