Can Llama 4 Scout 17B 16E run on MacBook Pro M4 Max 128GB?

YES — Tight Fit

A76Great

Estimated from fit model

Llama 4 Scout 17B 16E needs ~84.1 GB VRAM. MacBook Pro M4 Max 128GB has 92.2 GB. With Q4_K_M quantization, expect ~13 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: MediumStack: StandardBottleneck: Balanced

Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 84.1 GB, 13.2 tok/s, Tight fit

84.1 GB required92.2 GB available

91% VRAM used

Fit status

Tight fit

Decode

13.2 tok/s

TTFT

14718 ms

Safe context

60K

Memory

84.1 GB / 92.2 GB

Memory breakdown

Weights66.5 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom13.8 GB

See how fast it feels

See how fast it feelsLlama 4 Scout 17B 16E on MacBook Pro M4 Max 128GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.

Given information:
  - Speed = 60 mph (miles per hour)
  - Time  = 2.5 hours

Formula: Distance = Speed x Time

Calculation:
  Distance = 60 mph x 2.5 h
           = 150 miles

The train travels 150 miles.

Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.

Breakdown:
  - First half: 1.25 hours at 60 mph = 75 miles
  - Stop: 20 minutes (no distance)
  - Second half: 1.25 hours at 60 mph = 75 miles

Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph

The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 13.2 tok/s decode · 14.7s TTFT (warm) · 33 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Shared-memory contention still exists

The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Tight fit	13.2 tok/s	8028 ms	60K
Coding	A	Tight fit	13.2 tok/s	14718 ms	60K
Agentic Coding	A	Tight fit	13.2 tok/s	21409 ms	60K
Reasoning	A	Tight fit	13.2 tok/s	17394 ms	60K
RAG	A	Tight fit	13.2 tok/s	26761 ms	60K

Quantization options

How Llama 4 Scout 17B 16E (109B params) fits at each quantization level on MacBook Pro M4 Max 128GB (92.2 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	42.5 GB	Low	A74
Q3_K_S	3	53.4 GB	Low	A76
NVFP4	4	61.0 GB	Medium	A76
Q4_K_MBest for your GPU	4	66.5 GB	Medium	A76
Q5_K_M	5	78.5 GB	High	F0
Q6_K	6	89.4 GB	High	F0
Q8_0	8	116.6 GB	Very High	F0
F16	16	223.5 GB	Maximum	F0

Get started

Copy-paste commands to run Llama 4 Scout 17B 16E on your machine.

Run

lms load Llama-4-Scout-17B-16E-Instruct && lms server start

Your hardware

More models your MacBook Pro M4 Max 128GB can run

Model	Params	Grade	Decode
Devstral 2 123B Instruct	123B	S	8.2 tok/s
Qwen 3.5 122B A10B	122B	S	21.4 tok/s
Mistral Small 4 119B	119B	S	22.9 tok/s
GPT-OSS 120B	117B	S	9.2 tok/s
Command A 111B	111B	S	9.7 tok/s

Frequently asked questions

Can MacBook Pro M4 Max 128GB run Llama 4 Scout 17B 16E?

Yes, MacBook Pro M4 Max 128GB can run Llama 4 Scout 17B 16E with a A grade (Tight fit). Expected decode speed: 13.2 tok/s.

How much VRAM does Llama 4 Scout 17B 16E need?

Llama 4 Scout 17B 16E (109B parameters) requires approximately 84.1 GB of memory with Q4_K_M quantization.

What is the best quantization for Llama 4 Scout 17B 16E?

The recommended quantization for Llama 4 Scout 17B 16E is Q4_K_M, which balances quality and memory efficiency.

What speed will Llama 4 Scout 17B 16E run at on MacBook Pro M4 Max 128GB?

On MacBook Pro M4 Max 128GB, Llama 4 Scout 17B 16E achieves approximately 13.2 tokens per second decode speed with a time-to-first-token of 14718ms using Q4_K_M quantization.

Can MacBook Pro M4 Max 128GB run Llama 4 Scout 17B 16E for coding?

For coding workloads, Llama 4 Scout 17B 16E on MacBook Pro M4 Max 128GB receives a A grade with 13.2 tok/s and 60K context.

What context window can Llama 4 Scout 17B 16E use on MacBook Pro M4 Max 128GB?

On MacBook Pro M4 Max 128GB, Llama 4 Scout 17B 16E can safely use up to 60K tokens of context. The model's official context limit is 10.5M, but available memory constrains the safe maximum.

Is unified memory on MacBook Pro M4 Max 128GB as fast as VRAM for Llama 4 Scout 17B 16E?

Not always. MacBook Pro M4 Max 128GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.

See all results for MacBook Pro M4 Max 128GB See all hardware for Llama 4 Scout 17B 16E

Embed this result▼

Paste this snippet into any page to show a live fit card.

<iframe src="https://willitrunai.com/embed/llama-4-scout-17b-16e-on-m4-max-128gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>

Preview: