Will It Run AI

Can Phi 3 Medium 14B run on RTX 2000 Ada 16GB?

YES — Tight Fit

B61Good
Estimated from fit model

Phi 3 Medium 14B needs ~14.4 GB VRAM. RTX 2000 Ada 16GB has 16.0 GB. With Q4_K_M quantization, expect ~28 tok/s.

Runtime: OllamaCapacity: TightBandwidth: LowStack: BasicBottleneck: Balanced
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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) — 14.4 GB, 27.6 tok/s, Tight fit
14.4 GB required16.0 GB available
90% VRAM used

Fit status

Tight fit

Decode

27.6 tok/s

TTFT

7027 ms

Safe context

24K

Memory

14.4 GB / 16.0 GB

Memory breakdown

Weights8.5 GB
KV Cache3.1 GB
Runtime1.2 GB
Headroom1.6 GB

See how fast it feels

See how fast it feelsPhi 3 Medium 14B on RTX 2000 Ada 16GB
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: 27.6 tok/s decode · 7.0s TTFT (warm) · 69 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

WorkloadGradeFitDecodeTTFTContext
ChatBRuns well27.6 tok/s3833 ms24K
CodingBTight fit27.6 tok/s7027 ms24K
Agentic CodingCVery compromised (needs ~0.7 GB host RAM)17.2 tok/s16345 ms24K
ReasoningBTight fit27.6 tok/s8304 ms24K
RAGCVery compromised (needs ~0.7 GB host RAM)17.2 tok/s20431 ms24K

Quantization options

How Phi 3 Medium 14B (14B params) fits at each quantization level on RTX 2000 Ada 16GB (16.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
5.5 GB
LowB60
Q3_K_S
3
6.9 GB
LowB62
NVFP4
4
7.8 GB
MediumB63
Q4_K_M
4
8.5 GB
MediumB62
Q5_K_M
5
10.1 GB
HighB62
Q6_KBest for your GPU
6
11.5 GB
HighB62
Q8_0
8
15.0 GB
Very HighF0
F16
16
28.7 GB
MaximumF0

Get started

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

Run

ollama run phi3:medium

Upgrade-Optionen

Hardware, die Phi 3 Medium 14B gut ausführt

NVIDIARTX 4000 Ada 20GBGünstige Wahl
20 GB VRAM (+4)360 GB/s (+72)
B
Raises estimated decode speed by about 28%.35.3 tok/s Dekodierung

Raises estimated decode speed by about 28%.

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

ca. $1,250 MSRP

NVIDIARTX 3090 24GBBestes Preis-Leistungs-Verhältnis
24 GB VRAM (+8)936 GB/s (+648)
B
Raises estimated decode speed by about 199%.82.5 tok/s Dekodierung

Raises estimated decode speed by about 199%.

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

ca. $1,499 MSRP

NVIDIARTX 4090 24GBNVIDIA-Upgrade
24 GB VRAM (+8)1008 GB/s (+720)
B
Raises estimated decode speed by about 249%.96.4 tok/s Dekodierung

Raises estimated decode speed by about 249%.

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

ca. $1,599 MSRP

Frequently asked questions

Can RTX 2000 Ada 16GB run Phi 3 Medium 14B?

Yes, RTX 2000 Ada 16GB can run Phi 3 Medium 14B with a B grade (Tight fit). Expected decode speed: 27.6 tok/s.

How much VRAM does Phi 3 Medium 14B need?

Phi 3 Medium 14B (14B parameters) requires approximately 14.4 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 2000 Ada 16GB?

On RTX 2000 Ada 16GB, Phi 3 Medium 14B achieves approximately 27.6 tokens per second decode speed with a time-to-first-token of 7027ms using Q4_K_M quantization.

Can RTX 2000 Ada 16GB run Phi 3 Medium 14B for coding?

For coding workloads, Phi 3 Medium 14B on RTX 2000 Ada 16GB receives a B grade with 27.6 tok/s and 24K context.

What context window can Phi 3 Medium 14B use on RTX 2000 Ada 16GB?

On RTX 2000 Ada 16GB, Phi 3 Medium 14B can safely use up to 24K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.

See all results for RTX 2000 Ada 16GBSee all hardware for Phi 3 Medium 14B
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