Can Llama 4 Maverick 17B 128E run on AMD Instinct MI350X 288GB?

YES — With Offload

S88Excellent

Estimated from fit model

Llama 4 Maverick 17B 128E needs ~276.6 GB VRAM. AMD Instinct MI350X 288GB has 288.0 GB. With Q4_K_M quantization, expect ~77 tok/s.

Runtime: llama.cppCapacity: OffloadBandwidth: 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) — 276.6 GB, 77.4 tok/s, Runs with offload

276.6 GB required288.0 GB available

96% VRAM used

Fit status

Runs with offload

Decode

77.4 tok/s

TTFT

2502 ms

Safe context

78K

Memory

276.6 GB / 288.0 GB

Memory breakdown

Weights244.0 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom28.8 GB

See how fast it feels

See how fast it feelsLlama 4 Maverick 17B 128E 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: 77.4 tok/s decode · 2.5s TTFT (warm) · 194 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Very little memory headroom

You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.

Best improvement path

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	S	Runs with offload	77.4 tok/s	1364 ms	78K
Coding	S	Runs with offload	77.4 tok/s	2502 ms	78K
Agentic Coding	S	Runs with offload	77.4 tok/s	3639 ms	78K
Reasoning	S	Runs with offload	77.4 tok/s	2956 ms	78K
RAG	S	Runs with offload	77.4 tok/s	4548 ms	78K

Quantization options

How Llama 4 Maverick 17B 128E (400B params) fits at each quantization level on AMD Instinct MI350X 288GB (288.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	156.0 GB	Low	A82
Q3_K_S	3	196.0 GB	Low	A82
NVFP4Best for your GPU	4	224.0 GB	Medium	A82
Q4_K_M	4	244.0 GB	Medium	F0
Q5_K_M	5	288.0 GB	High	F0
Q6_K	6	328.0 GB	High	F0
Q8_0	8	428.0 GB	Very High	F0
F16	16	820.0 GB	Maximum	F0

Get started

Copy-paste commands to run Llama 4 Maverick 17B 128E on your machine.

Run

lms load Llama-4-Maverick-17B-128E-Instruct && lms server start

Your hardware

More models your AMD Instinct MI350X 288GB can run

Model	Params	Grade	Decode	Capabilities
Qwen3-Coder 480B A35B Instruct	480B	A	35.3 tok/s

Frequently asked questions

Can AMD Instinct MI350X 288GB run Llama 4 Maverick 17B 128E?

Yes, AMD Instinct MI350X 288GB can run Llama 4 Maverick 17B 128E with a S grade (Runs with offload). Expected decode speed: 77.4 tok/s.

How much VRAM does Llama 4 Maverick 17B 128E need?

Llama 4 Maverick 17B 128E (400B parameters) requires approximately 276.6 GB of memory with Q4_K_M quantization.

What is the best quantization for Llama 4 Maverick 17B 128E?

The recommended quantization for Llama 4 Maverick 17B 128E is Q4_K_M, which balances quality and memory efficiency.

What speed will Llama 4 Maverick 17B 128E run at on AMD Instinct MI350X 288GB?

On AMD Instinct MI350X 288GB, Llama 4 Maverick 17B 128E achieves approximately 77.4 tokens per second decode speed with a time-to-first-token of 2502ms using Q4_K_M quantization.

Can AMD Instinct MI350X 288GB run Llama 4 Maverick 17B 128E for coding?

For coding workloads, Llama 4 Maverick 17B 128E on AMD Instinct MI350X 288GB receives a S grade with 77.4 tok/s and 78K context.

What context window can Llama 4 Maverick 17B 128E use on AMD Instinct MI350X 288GB?

On AMD Instinct MI350X 288GB, Llama 4 Maverick 17B 128E can safely use up to 78K tokens of context. The model's official context limit is 1.0M, but available memory constrains the safe maximum.

What should I upgrade first if Llama 4 Maverick 17B 128E feels slow on AMD Instinct MI350X 288GB?

Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

See all results for AMD Instinct MI350X 288GB See all hardware for Llama 4 Maverick 17B 128E

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