Can Phi 3 Medium 14B run on RTX 6000 Ada 48GB?
YES — Runs Great
Phi 3 Medium 14B needs ~17.6 GB VRAM. RTX 6000 Ada 48GB has 48.0 GB. With Q4_K_M quantization, expect ~99 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
99.1 tok/s
TTFT
1954 ms
Safe context
128K
Memory
17.6 GB / 48.0 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 | B | Runs well | 99.1 tok/s | 1066 ms | 128K |
| Coding | B | Runs well | 99.1 tok/s | 1954 ms | 128K |
| Agentic Coding | B | Runs well | 99.1 tok/s | 2842 ms | 128K |
| Reasoning | B | Runs well | 99.1 tok/s | 2309 ms | 128K |
| RAG | B | Runs well | 99.1 tok/s | 3552 ms | 128K |
Quantization options
How Phi 3 Medium 14B (14B params) fits at each quantization level on RTX 6000 Ada 48GB (48.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C53 |
Q3_K_S | 3 | 6.9 GB | Low | C53 |
NVFP4 | 4 | 7.8 GB | Medium | C53 |
Q4_K_M | 4 | 8.5 GB | Medium | C53 |
Q5_K_M | 5 | 10.1 GB | High | C54 |
Q6_K | 6 | 11.5 GB | High | C54 |
Q8_0 | 8 | 15.0 GB | Very High | B55 |
F16Best for your GPU | 16 | 28.7 GB | Maximum | B59 |
Get started
Copy-paste commands to run Phi 3 Medium 14B on your machine.
Run
ollama run phi3:medium