Can Phi-4-reasoning-plus 14B run on RTX 6000 Ada Laptop 16GB?
YES — Tight Fit
Phi-4-reasoning-plus 14B needs ~14.5 GB VRAM. RTX 6000 Ada Laptop 16GB has 16.0 GB. With Q4_K_M quantization, expect ~52 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
52.0 tok/s
TTFT
3726 ms
Safe context
24K
Memory
14.5 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 | 52.0 tok/s | 2032 ms | 24K |
| Coding | S | Tight fit | 52.0 tok/s | 3726 ms | 24K |
| Agentic Coding | A | Very compromised (needs ~0.8 GB host RAM) | 32.0 tok/s | 8799 ms | 24K |
| Reasoning | S | Tight fit | 52.0 tok/s | 4403 ms | 24K |
| RAG | A | Very compromised (needs ~0.8 GB host RAM) | 32.0 tok/s | 10999 ms |
Quantization options
How Phi-4-reasoning-plus 14B (14.699999809265137B params) fits at each quantization level on RTX 6000 Ada Laptop 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.7 GB | Low | S89 |
Q3_K_S | 3 | 7.2 GB | Low | S91 |
NVFP4 | 4 |
Get started
Copy-paste commands to run Phi-4-reasoning-plus 14B on your machine.
Run
ollama run phi4-reasoning