Which local LLM can be run on the Studio M4 Max 128GB?

Compare K2 Horizon 0.9B, Qwen3.8-Flash-Next with a 4K input and the recommended format for each hardware platform. Required memory varies by model and context length.

What is the local LLM computing power of the Studio M4 Max 128GB?

Expected to draw approximately 130W under sustained load, with an actual range estimated between 95–165W.

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.

Updated September 2026

Mac Studio M4 Max 128GB To pack 70B class into one vehicle. CUDA-specific tools cannot be used.

Suits people who want to compare a wide range from 70B-class to high-precision models in a single finished machine.

Speed and memory for the same model

Studio M4 Max 128GB · Qwen3.8 27B · local LLM speed and memory: Prompt processing · prefill 393–707 tok/s · Token generation · decode 27.9–60.4 tok/s; Required 17.86GB / Usable 114GB unified memory — 4,096 input tokens · single request · prompt cache off

Calculate speed with this configuration Method and evidence CC BY 4.0

Available memory: 114GB
Memory bandwidth: 546GB/s
Estimated sustained LLM load: About 130W
Korean price range (KRW): 780 × KRW 10,000–888 × KRW 10,000

Who it fits

70B class Q4
Simultaneous storage of multiple models
Large integrated memory

Skip it if

Memory is ample, but tasks that require CUDA-specific tools require separate confirmation.

Recommended format for each device 4K input

The model you will experience with this equipment

Basic decoding · Expected range

K2 Horizon 0.9B

Required 1.03GB · spare time

MLX 4-bit

Decode

762.3 ~ 844.8 tok/s

First token

0.52 to 1.0 seconds

Qwen3.8-Flash-Next

recommended

Required 107.13GB · titration

MLX 4-bit

Decode

34.2 ~ 48.1 tok/s

First token

4.4 ~ 8.6 s

speed tuning

Actual speed varies with runtime version, cooling, context length and quantization file.

purchase judgment

What tasks is it suitable for?

70B conversation

Suitable

Easy to load the large Q4 model from a single finished product.

Documents / RAG

comfortable

Large integrated memory keeps models and cache together.

Create image

Suitable

There is a lot of memory space, but you need to check for CUDA-only nodes.

The first thing to get stuck: It is strong for loading large models, but has fewer options for tasks that require a CUDA-specific kernel and multi-GPU scalability.
Configuration to check: M4 Max · Integrated memory 128GB · SSD 1TB or more
Criteria for spending more money: It is worth considering if you want to put a 70B class model in one vehicle. If you only use 35B or less, M4 Pro 48GB is economical.

On sales pages, look at memory before chips.

The model and speed assumptions above change if the product is not the 128GB configuration.

Frequently asked questions

Which local LLM can be run on the Studio M4 Max 128GB?: K2 Horizon 0.9B, Qwen3.8-Flash-Next and others with a 4K input and the recommended format. Required memory varies by model and context length.
What is the local LLM computing power of the Studio M4 Max 128GB?: Sustained load is about 130 W, with an actual range of 95–165 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.

35B balance

Mac mini M4 Pro 48GB

When you repeatedly read documents and edit code with a 27B model, each wait matters as well as capacity. This page uses the 20-core GPU, 48GB configuration. Distinguish it from less expensive listings with a 16-core GPU.

CUDA environment

DGX Spark 128GB

This is for handling a large model on one machine without splitting it across several graphics cards. You should have a reason to buy 128GB. If the model you need now fits in 24GB or 32GB, do not assume Spark will be faster just because it has more memory.

low price

Ryzen AI Max+ 395 128GB

It is attractive when you have large amounts of integrated memory at a low price and can handle runtime settings directly.