Can Phi 4 reasoning vision 15B run on NVIDIA A40 48GB?

YES — Runs Great

C48Usable

Estimated from fit model

Phi 4 reasoning vision 15B needs ~16.9 GB VRAM. NVIDIA A40 48GB has 48.0 GB. With Q4_K_M quantization, expect ~59 tok/s.

Runtime: OllamaCapacity: RoomyBandwidth: MediumStack: 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) — 16.9 GB, 59.3 tok/s, Runs well

16.9 GB required48.0 GB available

35% VRAM used

Fit status

Runs well

Decode

59.3 tok/s

TTFT

3263 ms

Safe context

299K

Memory

16.9 GB / 48.0 GB

Memory breakdown

Weights9.2 GB

KV Cache1.8 GB

Runtime1.2 GB

Headroom4.8 GB

See how fast it feels

See how fast it feelsPhi 4 reasoning vision 15B on NVIDIA A40 48GB
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: 59.3 tok/s decode · 3.3s TTFT (warm) · 148 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	59.3 tok/s	1780 ms	299K
Coding	C	Runs well	59.3 tok/s	3263 ms	299K
Agentic Coding	C	Runs well	59.3 tok/s	4746 ms	299K
Reasoning	C	Runs well	59.3 tok/s	3856 ms	299K
RAG	C	Runs well	59.3 tok/s	5933 ms	299K

Quantization options

How Phi 4 reasoning vision 15B (15B params) fits at each quantization level on NVIDIA A40 48GB (48.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.9 GB	Low	C42
Q3_K_S	3	7.4 GB	Low	C42
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

Upgrade options

Hardware that runs Phi 4 reasoning vision 15B well

AMD Instinct MI210 64GBBudget pick

64 GB VRAM (+16)1638 GB/s (+942)

Raises estimated decode speed by about 105%.121.7 tok/s decode

Raises estimated decode speed by about 105%.

Adds memory headroom for longer context windows and future model growth.

~$10,000 MSRP

Frequently asked questions

Can NVIDIA A40 48GB run Phi 4 reasoning vision 15B?

Yes, NVIDIA A40 48GB can run Phi 4 reasoning vision 15B with a C grade (Runs well). Expected decode speed: 59.3 tok/s.

How much VRAM does Phi 4 reasoning vision 15B need?

Phi 4 reasoning vision 15B (15B parameters) requires approximately 16.9 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi 4 reasoning vision 15B?

The recommended quantization for Phi 4 reasoning vision 15B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi 4 reasoning vision 15B run at on NVIDIA A40 48GB?

On NVIDIA A40 48GB, Phi 4 reasoning vision 15B achieves approximately 59.3 tokens per second decode speed with a time-to-first-token of 3263ms using Q4_K_M quantization.

Can NVIDIA A40 48GB run Phi 4 reasoning vision 15B for coding?

For coding workloads, Phi 4 reasoning vision 15B on NVIDIA A40 48GB receives a C grade with 59.3 tok/s and 299K context.

What context window can Phi 4 reasoning vision 15B use on NVIDIA A40 48GB?

On NVIDIA A40 48GB, Phi 4 reasoning vision 15B can safely use up to 299K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

See all results for NVIDIA A40 48GB See all hardware for Phi 4 reasoning vision 15B

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