Can Phi-4 14B run on NVIDIA T4 16GB?
YES — Tight Fit
Phi-4 14B needs ~14.4 GB VRAM. NVIDIA T4 16GB has 16.0 GB. With Q4_K_M quantization, expect ~24 tok/s.
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.
Select quantization to explore
Fit status
Tight fit
Decode
26.2 tok/s
TTFT
7394 ms
Safe context
16K
Memory
14.4 GB / 16.0 GB
Memory breakdown
See how fast it feels
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 | 24.4 tok/s | 7949 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 phi4Your hardware
More models your NVIDIA T4 16GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 14.7B | S | 24.9 tok/s | ||
| 21B | A | 22.3 tok/s | ||
| 22B | A | 8.7 tok/s | ||
| 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: 24.4 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 24.4 tokens per second decode speed with a time-to-first-token of 7949ms 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 24.4 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.
Embed this result▼
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/phi-4-14b-on-t4-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: