Adds memory headroom for longer context windows and future model growth.
〜$1,250 MSRP
Phi 3 Medium 14B needs ~14.1 GB VRAM. RTX 4080 Super 16GB has 16.0 GB. With Q4_K_M quantization, expect ~81 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
80.7 tok/s
TTFT
2398 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 | 80.7 tok/s | 1308 ms | 26K |
| Coding | B | Tight fit | 80.7 tok/s | 2398 ms | 26K |
| Agentic Coding | C | Runs with offload (needs ~0.6 GB host RAM) | 52.4 tok/s | 5378 ms | 26K |
| Reasoning | B | Tight fit | 80.7 tok/s | 2834 ms | 26K |
| RAG | C | Runs with offload (needs ~0.6 GB host RAM) | 52.4 tok/s | 6722 ms | 26K |
How Phi 3 Medium 14B (14B params) fits at each quantization level on RTX 4080 Super 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:mediumアップグレードオプション
Adds memory headroom for longer context windows and future model growth.
〜$1,250 MSRP
Adds memory headroom for longer context windows and future model growth.
〜$1,499 MSRP
Raises estimated decode speed by about 26%.
Adds memory headroom for longer context windows and future model growth.
〜$1,599 MSRP
Yes, RTX 4080 Super 16GB can run Phi 3 Medium 14B with a B grade (Tight fit). Expected decode speed: 80.7 tok/s.
Phi 3 Medium 14B (14B parameters) requires approximately 14.1 GB of memory with Q4_K_M quantization.
The recommended quantization for Phi 3 Medium 14B is Q4_K_M, which balances quality and memory efficiency.
On RTX 4080 Super 16GB, Phi 3 Medium 14B achieves approximately 80.7 tokens per second decode speed with a time-to-first-token of 2398ms using Q4_K_M quantization.
For coding workloads, Phi 3 Medium 14B on RTX 4080 Super 16GB receives a B grade with 80.7 tok/s and 26K context.
On RTX 4080 Super 16GB, Phi 3 Medium 14B can safely use up to 26K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/phi-3-medium-14b-on-rtx-4080-super-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
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