Can Phi 3 Medium 14B run on RTX 5000 Ada 32GB?

YES — Runs Great

B62Good

Estimated from fit model

Phi 3 Medium 14B needs ~16.0 GB VRAM. RTX 5000 Ada 32GB has 32.0 GB. With Q4_K_M quantization, expect ~58 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) — 16.0 GB, 58.0 tok/s, Runs well

16.0 GB required32.0 GB available

50% VRAM used

Fit status

Runs well

Decode

58.0 tok/s

TTFT

3338 ms

Safe context

100K

Memory

16.0 GB / 32.0 GB

Memory breakdown

Weights8.5 GB

KV Cache3.1 GB

Runtime1.2 GB

Headroom3.2 GB

See how fast it feels

See how fast it feelsPhi 3 Medium 14B on RTX 5000 Ada 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: 58.0 tok/s decode · 3.3s TTFT (warm) · 145 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	B	Runs well	58.0 tok/s	1821 ms	100K
Coding	B	Runs well	58.0 tok/s	3338 ms	100K
Agentic Coding	B	Runs well	58.0 tok/s	4855 ms	100K
Reasoning	B	Runs well	58.0 tok/s	3945 ms	100K
RAG	B	Runs well	58.0 tok/s	6068 ms	100K

Quantization options

How Phi 3 Medium 14B (14B params) fits at each quantization level on RTX 5000 Ada 32GB (32.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	C55
Q3_K_S	3	6.9 GB	Low	B55
NVFP4	4	7.8 GB	Medium	B56
Q4_K_M	4	8.5 GB	Medium	B56
Q5_K_M	5	10.1 GB	High	B57
Q6_K	6	11.5 GB	High	B57
Q8_0Best for your GPU	8	15.0 GB	Very High	B59
F16	16	28.7 GB	Maximum	F0

Get started

Copy-paste commands to run Phi 3 Medium 14B on your machine.

Run

ollama run phi3:medium

Frequently asked questions

Can RTX 5000 Ada 32GB run Phi 3 Medium 14B?

Yes, RTX 5000 Ada 32GB can run Phi 3 Medium 14B with a B grade (Runs well). Expected decode speed: 58.0 tok/s.

How much VRAM does Phi 3 Medium 14B need?

Phi 3 Medium 14B (14B parameters) requires approximately 16.0 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi 3 Medium 14B?

The recommended quantization for Phi 3 Medium 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi 3 Medium 14B run at on RTX 5000 Ada 32GB?

On RTX 5000 Ada 32GB, Phi 3 Medium 14B achieves approximately 58.0 tokens per second decode speed with a time-to-first-token of 3338ms using Q4_K_M quantization.

Can RTX 5000 Ada 32GB run Phi 3 Medium 14B for coding?

For coding workloads, Phi 3 Medium 14B on RTX 5000 Ada 32GB receives a B grade with 58.0 tok/s and 100K context.

What context window can Phi 3 Medium 14B use on RTX 5000 Ada 32GB?

On RTX 5000 Ada 32GB, Phi 3 Medium 14B can safely use up to 100K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.

See all results for RTX 5000 Ada 32GB See all hardware for Phi 3 Medium 14B

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