Can Phi-4-reasoning-plus 14B run on NVIDIA A800 80GB?
YES — Runs Great
Phi-4-reasoning-plus 14B needs ~21.2 GB VRAM. NVIDIA A800 80GB has 80.0 GB. With Q4_K_M quantization, expect ~168 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
Runs well
Decode
180.9 tok/s
TTFT
1070 ms
Safe context
33K
Memory
21.2 GB / 80.0 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 | 180.9 tok/s | 584 ms | 33K |
| Coding | S | Runs well | 168.3 tok/s | 1150 ms | 33K |
| Agentic Coding | S | Runs well | 180.9 tok/s | 1556 ms | 33K |
| Reasoning | S | Runs well | 180.9 tok/s | 1265 ms | 33K |
| RAG | S | Runs well | 180.9 tok/s | 1945 ms | 33K |
Quantization options
How Phi-4-reasoning-plus 14B (14.699999809265137B params) fits at each quantization level on NVIDIA A800 80GB (80.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.7 GB | Low | A79 |
Q3_K_S | 3 | 7.2 GB | Low | A80 |
NVFP4 | 4 |
Get started
Copy-paste commands to run Phi-4-reasoning-plus 14B on your machine.
Run
ollama run phi4-reasoningYour hardware
