Raises estimated decode speed by about 134%.
~$1,499 MSRP
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VOOZH | about |
Phi 3 Medium 14B needs ~14.8 GB VRAM. RTX 4000 Ada 20GB has 20.0 GB. With Q4_K_M quantization, expect ~33 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
35.3 tok/s
TTFT
5477 ms
Safe context
43K
Memory
14.8 GB / 20.0 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 | 32.9 tok/s | 3212 ms | 43K |
| Coding | B | Runs well | 32.9 tok/s | 5888 ms | 43K |
| Agentic Coding | B | Tight fit | 32.9 tok/s | 8564 ms | 43K |
| Reasoning | B | Runs well | 32.9 tok/s | 6959 ms | 43K |
| RAG | B | Tight fit | 32.9 tok/s | 10705 ms | 43K |
How Phi 3 Medium 14B (14B params) fits at each quantization level on RTX 4000 Ada 20GB (20.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | B58 |
Q3_K_S | 3 | 6.9 GB | Low | B59 |
NVFP4 | 4 |
Copy-paste commands to run Phi 3 Medium 14B on your machine.
Run
ollama run phi3:mediumUpgrade options
Raises estimated decode speed by about 134%.
~$1,499 MSRP
Raises estimated decode speed by about 173%.
~$1,599 MSRP
Raises estimated decode speed by about 101%.
~$1,599 MSRP
7.8 GB |
| Medium |
| B60 |
Q4_K_M | 4 | 8.5 GB | Medium | B61 |
Q5_K_M | 5 | 10.1 GB | High | B62 |
Q6_K | 6 | 11.5 GB | High | B62 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | B61 |
F16 | 16 | 28.7 GB | Maximum | F0 |