Can Qwen 3 14B run on RTX 6000 Ada Laptop 16GB?
YES — Tight Fit
Qwen 3 14B needs ~13.5 GB VRAM. RTX 6000 Ada Laptop 16GB has 16.0 GB. With Q4_K_M quantization, expect ~61 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
60.9 tok/s
TTFT
3181 ms
Safe context
33K
Memory
13.5 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 | 60.9 tok/s | 1735 ms | 33K |
| Coding | S | Tight fit | 60.9 tok/s | 3181 ms | 33K |
| Agentic Coding | S | Runs with offload | 60.9 tok/s | 4627 ms | 33K |
| Reasoning | S | Tight fit | 60.9 tok/s | 3759 ms | 33K |
| RAG | S | Runs with offload | 60.9 tok/s | 5784 ms | 33K |
Quantization options
How Qwen 3 14B (14B params) fits at each quantization level on RTX 6000 Ada Laptop 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