Can Phi-4-reasoning-plus 14B run on RTX 5080 Laptop 16GB?
YES — Tight Fit
Phi-4-reasoning-plus 14B needs ~14.8 GB VRAM. RTX 5080 Laptop 16GB has 16.0 GB. With Q4_K_M quantization, expect ~72 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
77.3 tok/s
TTFT
2503 ms
Safe context
22K
Memory
14.8 GB / 16.0 GB
Memory breakdown
See how fast it feels
What limits this setup
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Best improvement path
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | S | Tight fit | 71.9 tok/s | 1468 ms | 22K |
| Coding | S | Tight fit | 71.9 tok/s | 2691 ms | 22K |
| Agentic Coding | A | Very compromised | 42.8 tok/s | 6586 ms | 22K |
| Reasoning | S | Tight fit | 71.9 tok/s | 3180 ms | 22K |
| RAG | A | Very compromised | 42.8 tok/s | 8233 ms | 22K |
Quantization options
How Phi-4-reasoning-plus 14B (14.699999809265137B params) fits at each quantization level on RTX 5080 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