Can Phi-4 14B run on NVIDIA T4 16GB?

YES — Tight Fit

A81Great

Estimated from fit model

Phi-4 14B needs ~14.4 GB VRAM. NVIDIA T4 16GB has 16.0 GB. With Q4_K_M quantization, expect ~26 tok/s.

Runtime: OllamaCapacity: TightBandwidth: LowStack: 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) — 14.4 GB, 26.2 tok/s, Tight fit

14.4 GB required16.0 GB available

90% VRAM used

Fit status

Tight fit

Decode

26.2 tok/s

TTFT

7394 ms

Safe context

16K

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-4 14B on NVIDIA T4 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: 26.2 tok/s decode · 7.4s TTFT (warm) · 66 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Older PCIe generation

PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.

Best improvement path

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	A	Runs well	26.2 tok/s	4033 ms	16K
Coding	A	Tight fit	26.2 tok/s	7394 ms	16K
Agentic Coding	B	Very compromised (needs ~0.7 GB host RAM)	15.8 tok/s	17825 ms	16K
Reasoning	A	Tight fit	26.2 tok/s	8739 ms	16K
RAG	B	Very compromised (needs ~0.7 GB host RAM)	15.8 tok/s	22281 ms	16K

Quantization options

How Phi-4 14B (14B params) fits at each quantization level on NVIDIA T4 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	5.5 GB	Low	A81
Q3_K_S	3	6.9 GB	Low	A82
NVFP4	4	7.8 GB	Medium	A83
Q4_K_M	4	8.5 GB	Medium	A83
Q5_K_M	5	10.1 GB	High	A83
Q6_KBest for your GPU	6	11.5 GB	High	A82
Q8_0	8	15.0 GB	Very High	F0
F16	16	28.7 GB	Maximum	F0

Get started

Copy-paste commands to run Phi-4 14B on your machine.

Run

ollama run phi4

Your hardware

More models your NVIDIA T4 16GB can run

Model	Params	Grade	Decode
Phi-4-reasoning-plus 14B	14.7B	S	24.9 tok/s
GPT-OSS 20B	21B	A	22.3 tok/s
Codestral 2 25.08	22B	A	8.7 tok/s
CogVLM2 19B	19B	A	12.6 tok/s

Frequently asked questions

Can NVIDIA T4 16GB run Phi-4 14B?

Yes, NVIDIA T4 16GB can run Phi-4 14B with a A grade (Tight fit). Expected decode speed: 26.2 tok/s.

How much VRAM does Phi-4 14B need?

Phi-4 14B (14B parameters) requires approximately 14.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi-4 14B?

The recommended quantization for Phi-4 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi-4 14B run at on NVIDIA T4 16GB?

On NVIDIA T4 16GB, Phi-4 14B achieves approximately 26.2 tokens per second decode speed with a time-to-first-token of 7394ms using Q4_K_M quantization.

Can NVIDIA T4 16GB run Phi-4 14B for coding?

For coding workloads, Phi-4 14B on NVIDIA T4 16GB receives a A grade with 26.2 tok/s and 16K context.

What context window can Phi-4 14B use on NVIDIA T4 16GB?

On NVIDIA T4 16GB, Phi-4 14B can safely use up to 16K tokens of context. The model's official context limit is 16K, but available memory constrains the safe maximum.

See all results for NVIDIA T4 16GB See all hardware for Phi-4 14B

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Preview:

Workload

Grade

Fit

Decode

TTFT

Context

Chat

Runs well

26.2 tok/s

4033 ms

16K

Coding

Tight fit

26.2 tok/s

7394 ms

16K

Agentic Coding

Very compromised (needs ~0.7 GB host RAM)

15.8 tok/s

17825 ms

16K

Reasoning

Tight fit

26.2 tok/s

8739 ms

16K

RAG

Very compromised (needs ~0.7 GB host RAM)

15.8 tok/s

22281 ms

16K

Quant

Bits

VRAM

Quality

Fit

Q2_K

5.5 GB

Low

A81

Q3_K_S

6.9 GB

Low

A82

NVFP4

7.8 GB

Medium

A83

Q4_K_M

8.5 GB

Medium

A83

Q5_K_M

10.1 GB

High

A83

Q6_KBest for your GPU

11.5 GB

High

A82

Q8_0

15.0 GB

Very High

F16

28.7 GB

Maximum

Model

Params

Grade

Decode

Capabilities

Phi-4-reasoning-plus 14B

14.7B

24.9 tok/s

GPT-OSS 20B

21B

22.3 tok/s

Codestral 2 25.08

22B

8.7 tok/s

CogVLM2 19B

19B

12.6 tok/s

Frequently asked questions

Can NVIDIA T4 16GB run Phi-4 14B?

Yes, NVIDIA T4 16GB can run Phi-4 14B with a A grade (Tight fit). Expected decode speed: 26.2 tok/s.

How much VRAM does Phi-4 14B need?

Phi-4 14B (14B parameters) requires approximately 14.4 GB of memory with Q4_K_M quantization.

What is the best quantization for Phi-4 14B?

The recommended quantization for Phi-4 14B is Q4_K_M, which balances quality and memory efficiency.

What speed will Phi-4 14B run at on NVIDIA T4 16GB?

On NVIDIA T4 16GB, Phi-4 14B achieves approximately 26.2 tokens per second decode speed with a time-to-first-token of 7394ms using Q4_K_M quantization.

Can NVIDIA T4 16GB run Phi-4 14B for coding?

For coding workloads, Phi-4 14B on NVIDIA T4 16GB receives a A grade with 26.2 tok/s and 16K context.

What context window can Phi-4 14B use on NVIDIA T4 16GB?

On NVIDIA T4 16GB, Phi-4 14B can safely use up to 16K tokens of context. The model's official context limit is 16K, but available memory constrains the safe maximum.