Can Qwen 3 14B run on RTX 2000 Ada 16GB?
YES — Tight Fit
Qwen 3 14B needs ~13.8 GB VRAM. RTX 2000 Ada 16GB has 16.0 GB. With Q4_K_M quantization, expect ~26 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
27.7 tok/s
TTFT
6994 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.
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 | S | Runs well | 27.7 tok/s | 3815 ms | 31K |
| Coding | S | Tight fit | 25.6 tok/s | 7554 ms | 31K |
| Agentic Coding | S | Runs with offload (needs ~0.1 GB host RAM) | 20.2 tok/s | 13965 ms | 31K |
| Reasoning | S | Tight fit | 27.7 tok/s | 8266 ms | 31K |
| RAG | S | Runs with offload (needs ~0.1 GB host RAM) | 20.2 tok/s | 17456 ms |
Quantization options
How Qwen 3 14B (14B params) fits at each quantization level on RTX 2000 Ada 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