Can Llama 4 Maverick 17B 128E run on RTX 5090 32GB?

NO — Won't Fit

F0Won't run

○Estimated from fit model

Llama 4 Maverick 17B 128E needs ~251.0 GB but RTX 5090 32GB only has 32.0 GB. Try a smaller quantization or lighter model.

Runtime: llama.cppCapacity: No fitBandwidth: HighStack: StandardBottleneck: Memory capacity

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) — 251.0 GB, exceeds 32.0 GB available

251.0 GB required32.0 GB available

784% VRAM needed

219.0 GB over capacity — needs offload or smaller quantization

Fit status

Too heavy

Decode

2.4 tok/s

TTFT

81117 ms

Safe context

Memory

251.0 GB / 32.0 GB

Offload

90%

Memory breakdown

Weights244.0 GB

KV Cache2.9 GB

Runtime0.9 GB

Headroom3.2 GB

See how fast it feels

With memory offload — actual speed may be lower

See how fast it feelsLlama 4 Maverick 17B 128E on RTX 5090 32GB
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: 2.4 tok/s decode · 81.1s TTFT (warm) · 6 tok/s prefill

What limits this setup

Usable VRAM is the main blocker for this model.

Not enough usable memory

The model needs 251.0 GB, but this setup only exposes 32.0 GB of usable VRAM.

Best improvement path

Add more VRAM headroom

The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	F	Too heavy	2.4 tok/s	44246 ms	4K
Coding	F	Too heavy	2.4 tok/s	81117 ms	4K
Agentic Coding	F	Too heavy	2.4 tok/s	117989 ms	4K
Reasoning	F	Too heavy	2.4 tok/s	95866 ms	4K
RAG	F	Too heavy	2.4 tok/s	147486 ms	4K

Quantization options

How Llama 4 Maverick 17B 128E (400B params) fits at each quantization level on RTX 5090 32GB (32.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	156.0 GB	Low	F0
Q3_K_S	3	196.0 GB	Low	F0
NVFP4	4	224.0 GB	Medium	F0
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