Can Llama 4 Scout 17B 16E run on Mac Studio M3 Ultra 256GB?

YES — Runs Great

A76Great

Estimated from fit model

Llama 4 Scout 17B 16E needs ~98.0 GB VRAM. Mac Studio M3 Ultra 256GB has 184.3 GB. With Q4_K_M quantization, expect ~21 tok/s.

Runtime: llama.cppCapacity: RoomyBandwidth: HighStack: 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) — 98.0 GB, 21.3 tok/s, Runs well

98.0 GB required184.3 GB available

53% VRAM used

Fit status

Runs well

Decode

21.3 tok/s

TTFT

9091 ms

Safe context

488K

Memory

98.0 GB / 184.3 GB

Memory breakdown

Weights66.5 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom27.6 GB

See how fast it feels

See how fast it feelsLlama 4 Scout 17B 16E on Mac Studio M3 Ultra 256GB
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: 21.3 tok/s decode · 9.1s TTFT (warm) · 53 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	Runs well	21.3 tok/s	4959 ms	488K
Coding	A	Runs well	21.3 tok/s	9091 ms	488K
Agentic Coding	A	Runs well	21.3 tok/s	13223 ms	488K
Reasoning	A	Runs well	21.3 tok/s	10744 ms	488K
RAG	A	Runs well	21.3 tok/s	16529 ms	488K

Quantization options

How Llama 4 Scout 17B 16E (109B params) fits at each quantization level on Mac Studio M3 Ultra 256GB (184.3 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	42.5 GB	Low	B69
Q3_K_S	3	53.4 GB	Low	B70
NVFP4	4	61.0 GB	Medium	A71
Q4_K_M	4	66.5 GB	Medium	A71
Q5_K_M	5	78.5 GB	High	A73
Q6_K	6	89.4 GB	High	A74
Q8_0Best for your GPU	8	116.6 GB	Very High	A76
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 Mac Studio M3 Ultra 256GB can run

Model	Params	Grade	Decode
Devstral 2 123B Instruct	123B	S	8.1 tok/s
Qwen 3.5 122B A10B	122B	S	34.7 tok/s
DeepSeek V4 Flash	284B	S	17.8 tok/s
Mistral Small 4 119B	119B	S	37.6 tok/s
GPT-OSS 120B	117B	S	8.5 tok/s

Frequently asked questions

Can Mac Studio M3 Ultra 256GB run Llama 4 Scout 17B 16E?

Yes, Mac Studio M3 Ultra 256GB can run Llama 4 Scout 17B 16E with a A grade (Runs well). Expected decode speed: 21.3 tok/s.

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

Llama 4 Scout 17B 16E (109B parameters) requires approximately 98.0 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 Mac Studio M3 Ultra 256GB?

On Mac Studio M3 Ultra 256GB, Llama 4 Scout 17B 16E achieves approximately 21.3 tokens per second decode speed with a time-to-first-token of 9091ms using Q4_K_M quantization.

Can Mac Studio M3 Ultra 256GB run Llama 4 Scout 17B 16E for coding?

For coding workloads, Llama 4 Scout 17B 16E on Mac Studio M3 Ultra 256GB receives a A grade with 21.3 tok/s and 488K context.

What context window can Llama 4 Scout 17B 16E use on Mac Studio M3 Ultra 256GB?

On Mac Studio M3 Ultra 256GB, Llama 4 Scout 17B 16E can safely use up to 488K tokens of context. The model's official context limit is 10.5M, but available memory constrains the safe maximum.

Is unified memory on Mac Studio M3 Ultra 256GB as fast as VRAM for Llama 4 Scout 17B 16E?

Not always. Mac Studio M3 Ultra 256GB 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 Mac Studio M3 Ultra 256GB See all hardware for Llama 4 Scout 17B 16E

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