Can Phi 4 reasoning vision 15B run on NVIDIA A100 40GB?

YES — Runs Great

C50Usable

○Estimated from fit model

Phi 4 reasoning vision 15B needs ~16.1 GB VRAM. NVIDIA A100 40GB has 40.0 GB. With Q4_K_M quantization, expect ~143 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: HighStack: BasicBottleneck: 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) — 16.1 GB, 142.8 tok/s, Runs well

16.1 GB required40.0 GB available

40% VRAM used

Fit status

Runs well

Decode

142.8 tok/s

TTFT

1356 ms

Safe context

233K

Memory

16.1 GB / 40.0 GB

Memory breakdown

Weights9.2 GB

KV Cache1.8 GB

Runtime1.2 GB

Headroom4.0 GB

See how fast it feels

See how fast it feelsPhi 4 reasoning vision 15B on NVIDIA A100 40GB
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: 142.8 tok/s decode · 1.4s TTFT (warm) · 357 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	C	Runs well	142.8 tok/s	740 ms	233K
Coding	C	Runs well	142.8 tok/s	1356 ms	233K
Agentic Coding	C	Runs well	142.8 tok/s	1973 ms	233K
Reasoning	C	Runs well	142.8 tok/s	1603 ms	233K
RAG	C	Runs well	142.8 tok/s	2466 ms	233K

Quantization options

How Phi 4 reasoning vision 15B (15B params) fits at each quantization level on NVIDIA A100 40GB (40.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.9 GB	Low	C43
Q3_K_S	3	7.4 GB	Low	C43
NVFP4	4

Get started

Copy-paste commands to run Phi 4 reasoning vision 15B on your machine.

Run

lms load hf-jamesburton--phi-4-reasoning-vision-15b-gguf && lms server start

Frequently asked questions

See all results for NVIDIA A100 40GB See all hardware for Phi 4 reasoning vision 15B

URL: https://willitrunai.com/can-run/hf-jamesburton--phi-4-reasoning-vision-15b-gguf-on-a100-40gb

⇱