Raises estimated decode speed by about 246%.
Adds memory headroom for longer context windows and future model growth.
~$10,000 MSRP
![]() |
VOOZH | about |
Phi 3 Medium 14B needs ~15.7 GB VRAM. Radeon AI PRO R9700 32GB has 32.0 GB. With Q4_K_M quantization, expect ~44 tok/s.
Operating mode
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
47.5 tok/s
TTFT
4073 ms
Safe context
102K
Memory
15.7 GB / 32.0 GB
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.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 44.2 tok/s | 2388 ms | 102K |
| Coding | B | Runs well | 44.2 tok/s | 4379 ms | 102K |
| Agentic Coding | B | Runs well | 44.2 tok/s | 6369 ms | 102K |
| Reasoning | B | Runs well | 44.2 tok/s | 5175 ms | 102K |
| RAG | B | Runs well | 44.2 tok/s | 7961 ms | 102K |
How Phi 3 Medium 14B (14B params) fits at each quantization level on Radeon AI PRO R9700 32GB (32.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | C55 |
Q3_K_S | 3 | 6.9 GB | Low | B55 |
NVFP4 | 4 |
Copy-paste commands to run Phi 3 Medium 14B on your machine.
Run
ollama run phi3:mediumUpgrade options
7.8 GB |
| Medium |
| B56 |
Q4_K_M | 4 | 8.5 GB | Medium | B56 |
Q5_K_M | 5 | 10.1 GB | High | B57 |
Q6_K | 6 | 11.5 GB | High | B57 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | B59 |
F16 | 16 | 28.7 GB | Maximum | F0 |