Can Llama 4 Scout 17B 16E run on AMD Instinct MI250X 128GB?

YES — Runs Great

A84Great

○Estimated from fit model

Llama 4 Scout 17B 16E needs ~83.1 GB VRAM. AMD Instinct MI250X 128GB has 128.0 GB. With Q4_K_M quantization, expect ~95 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) — 83.1 GB, 95.4 tok/s, Runs well

83.1 GB required128.0 GB available

65% VRAM used

Fit status

Runs well

Decode

95.4 tok/s

TTFT

2028 ms

Safe context

261K

Memory

83.1 GB / 128.0 GB

Memory breakdown

Weights66.5 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom12.8 GB

See how fast it feels

See how fast it feelsLlama 4 Scout 17B 16E on AMD Instinct MI250X 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: 95.4 tok/s decode · 2.0s TTFT (warm) · 239 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	95.4 tok/s	1106 ms	261K
Coding	A	Runs well	95.4 tok/s	2028 ms	261K
Agentic Coding	A	Runs well	95.4 tok/s	2950 ms	261K
Reasoning	A	Runs well	95.4 tok/s	2397 ms	261K
RAG	A	Runs well	95.4 tok/s	3688 ms	261K

Quantization options

How Llama 4 Scout 17B 16E (109B params) fits at each quantization level on AMD Instinct MI250X 128GB (128.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	42.5 GB	Low	A71
Q3_K_S	3	53.4 GB	Low	A73
NVFP4	4	61.0 GB	Medium	A74
Q4_K_M	4	66.5 GB	Medium	A75
Q5_K_M	5	78.5 GB	High	A76
Q6_KBest for your GPU	6	89.4 GB	High	A76
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 AMD Instinct MI250X 128GB can run

Model	Params	Grade	Decode
👁 Mistral Devstral 2 123B Instruct	123B	S	36.2 tok/s
👁 Alibaba Qwen 3.5 122B A10B	122B	S	100.3 tok/s
👁 Mistral Mistral Small 4 119B	119B	S	108.8 tok/s
👁 OpenAI GPT-OSS 120B	117B	S	38 tok/s
👁 Cohere Command A 111B	111B	S	40.2 tok/s

Frequently asked questions

See all results for AMD Instinct MI250X 128GB See all hardware for Llama 4 Scout 17B 16E

URL: https://willitrunai.com/can-run/llama-4-scout-17b-16e-on-instinct-mi250x-128gb

⇱ Llama 4 Scout 17B 16E on AMD Instinct MI250X 128GB? YES