Can Qwen 3 14B run on NVIDIA T4 16GB?
YES — Tight Fit
Qwen 3 14B needs ~13.8 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
26.3 tok/s
TTFT
7360 ms
Safe context
31K
Memory
13.8 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 | S | Runs well | 26.3 tok/s | 4015 ms | 31K |
| Coding | S | Tight fit | 24.4 tok/s | 7949 ms | 31K |
| Agentic Coding | S | Runs with offload (needs ~0.1 GB host RAM) | 18.6 tok/s | 15129 ms | 31K |
| Reasoning | S | Tight fit | 26.3 tok/s | 8698 ms | 31K |
| RAG | S | Runs with offload (needs ~0.1 GB host RAM) | 18.6 tok/s | 18912 ms |
Quantization options
How Qwen 3 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 | S90 |
Q3_K_S | 3 | 6.9 GB | Low | S91 |
NVFP4 | 4 |
Get started
Copy-paste commands to run Qwen 3 14B on your machine.
Run
ollama run qwen3