Raises estimated decode speed by about 27%.
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 ~14.1 GB VRAM. RTX 4060 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~28 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
27.8 tok/s
TTFT
6967 ms
Safe context
26K
Memory
14.1 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 | 27.8 tok/s | 3800 ms | 26K |
| Coding | B | Tight fit | 27.8 tok/s | 6967 ms | 26K |
| Agentic Coding | C | Runs with offload (needs ~0.6 GB host RAM) | 18.0 tok/s | 15625 ms | 26K |
| Reasoning | B | Tight fit | 27.8 tok/s | 8234 ms | 26K |
| RAG | C | Runs with offload (needs ~0.6 GB host RAM) | 18.0 tok/s | 19531 ms | 26K |
How Phi 3 Medium 14B (14B params) fits at each quantization level on RTX 4060 Ti 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
Raises estimated decode speed by about 27%.
Adds memory headroom for longer context windows and future model growth.
~$1,250 MSRP
Raises estimated decode speed by about 191%.
Adds memory headroom for longer context windows and future model growth.
~$1,499 MSRP
Raises estimated decode speed by about 264%.
Adds memory headroom for longer context windows and future model growth.
~$1,599 MSRP