Phi 3 Medium 14B needs ~15.2 GB VRAM. RTX A5000 24GB has 24.0 GB. With Q4_K_M quantization, expect ~68 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
67.7 tok/s
TTFT
2861 ms
Safe context
62K
Memory
15.2 GB / 24.0 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 | 67.7 tok/s | 1560 ms | 62K |
| Coding | B | Runs well | 67.7 tok/s | 2861 ms | 62K |
| Agentic Coding | B | Runs well | 67.7 tok/s | 4161 ms | 62K |
| Reasoning | B | Runs well | 67.7 tok/s | 3381 ms | 62K |
| RAG | B | Runs well | 67.7 tok/s | 5202 ms | 62K |
How Phi 3 Medium 14B (14B params) fits at each quantization level on RTX A5000 24GB (24.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.5 GB | Low | B57 |
Q3_K_S | 3 | 6.9 GB | Low | B58 |
NVFP4 | 4 | 7.8 GB | Medium | B58 |
Q4_K_M | 4 | 8.5 GB | Medium | B59 |
Q5_K_M | 5 | 10.1 GB | High | B60 |
Q6_K | 6 | 11.5 GB | High | B61 |
Q8_0Best for your GPU | 8 | 15.0 GB | Very High | B61 |
F16 | 16 | 28.7 GB | Maximum | F0 |
Copy-paste commands to run Phi 3 Medium 14B on your machine.
Run
ollama run phi3:mediumYes, RTX A5000 24GB can run Phi 3 Medium 14B with a B grade (Runs well). Expected decode speed: 67.7 tok/s.
Phi 3 Medium 14B (14B parameters) requires approximately 15.2 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 A5000 24GB, Phi 3 Medium 14B achieves approximately 67.7 tokens per second decode speed with a time-to-first-token of 2861ms using Q4_K_M quantization.
For coding workloads, Phi 3 Medium 14B on RTX A5000 24GB receives a B grade with 67.7 tok/s and 62K context.
On RTX A5000 24GB, Phi 3 Medium 14B can safely use up to 62K 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-a5000-24gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: