Adds memory headroom for longer context windows and future model growth.
~$1,250 MSRP
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VOOZH | about |
Phi 3 Medium 14B needs ~14.4 GB VRAM. RTX A4000 16GB has 16.0 GB. With Q4_K_M quantization, expect ~40 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
Tight fit
Decode
39.5 tok/s
TTFT
4904 ms
Safe context
24K
Memory
14.4 GB / 16.0 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 | 39.5 tok/s | 2675 ms | 24K |
| Coding | B | Tight fit | 39.5 tok/s | 4904 ms | 24K |
| Agentic Coding | C | Very compromised (needs ~0.7 GB host RAM) | 24.7 tok/s | 11408 ms | 24K |
| Reasoning | B | Tight fit | 39.5 tok/s | 5796 ms | 24K |
| RAG | C | Very compromised (needs ~0.7 GB host RAM) | 24.7 tok/s | 14260 ms | 24K |
How Phi 3 Medium 14B (14B params) fits at each quantization level on RTX A4000 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | B60 |
Q3_K_S | 3 | 6.9 GB | Low | B62 |
NVFP4 | 4 | 7.8 GB | Medium | B63 |
Q4_K_M | 4 | 8.5 GB | Medium | B62 |
Q5_K_M | 5 | 10.1 GB | High | B62 |
Q6_KBest for your GPU | 6 | 11.5 GB | High | B62 |
Q8_0 | 8 | 15.0 GB | Very High | F0 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Copy-paste commands to run Phi 3 Medium 14B on your machine.
Run
ollama run phi3:mediumUpgrade options
Adds memory headroom for longer context windows and future model growth.
~$1,250 MSRP
Raises estimated decode speed by about 109%.
Adds memory headroom for longer context windows and future model growth.
~$1,499 MSRP
Raises estimated decode speed by about 144%.
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP