Can Llama 4 Scout 17B 16E run on AMD Instinct MI350X 288GB?

YES — Runs Great

A77Great

○Estimated from fit model

Llama 4 Scout 17B 16E needs ~99.1 GB VRAM. AMD Instinct MI350X 288GB has 288.0 GB. With Q4_K_M quantization, expect ~223 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) — 99.1 GB, 223.3 tok/s, Runs well

99.1 GB required288.0 GB available

34% VRAM used

Fit status

Runs well

Decode

223.3 tok/s

TTFT

867 ms

Safe context

1.0M

Memory

99.1 GB / 288.0 GB

Memory breakdown

Weights66.5 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom28.8 GB

See how fast it feels

See how fast it feelsLlama 4 Scout 17B 16E on AMD Instinct MI350X 288GB
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: 223.3 tok/s decode · 867ms TTFT (warm) · 558 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

No major red flags

This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	223.3 tok/s	473 ms	1.0M
Coding	A	Runs well	223.3 tok/s	867 ms	1.0M
Agentic Coding	A	Runs well	223.3 tok/s	1261 ms	1.0M
Reasoning	A	Runs well	223.3 tok/s	1025 ms	1.0M
RAG	A	Runs well	223.3 tok/s	1576 ms	1.0M

Quantization options

How Llama 4 Scout 17B 16E (109B params) fits at each quantization level on AMD Instinct MI350X 288GB (288.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	42.5 GB	Low	B67
Q3_K_S	3	53.4 GB	Low	B67
NVFP4	4

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 AMD Instinct MI350X 288GB can run

Model	Params	Grade	Decode	Capabilities
👁 Alibaba Qwen 3.5 397B A17B	397B	S	78.9 tok/s
👁 Mistral Devstral 2 123B Instruct	123B	S

Frequently asked questions

See all results for AMD Instinct MI350X 288GB See all hardware for Llama 4 Scout 17B 16E

URL: https://willitrunai.com/can-run/llama-4-scout-17b-16e-on-instinct-mi350x-288gb

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