Phi 3 Mini 3.8B needs ~10.7 GB VRAM. RTX 4060 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~61 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
60.8 tok/s
TTFT
3184 ms
Safe context
31K
Memory
10.7 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 | 60.8 tok/s | 1737 ms | 31K |
| Coding | A | Runs well | 60.8 tok/s | 3184 ms | 31K |
| Agentic Coding | B | Runs with offload (needs ~0.1 GB host RAM) | 58.4 tok/s | 4823 ms | 31K |
| Reasoning | A | Runs well | 60.8 tok/s | 3763 ms | 31K |
| RAG | B | Runs with offload (needs ~0.1 GB host RAM) | 58.4 tok/s | 6029 ms | 31K |
How Phi 3 Mini 3.8B (3.799999952316284B params) fits at each quantization level on RTX 4060 Ti 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.5 GB | Low | B63 |
Q3_K_S | 3 | 1.9 GB | Low | B63 |
NVFP4 | 4 | 2.1 GB | Medium | B63 |
Q4_K_M | 4 | 2.3 GB | Medium | B63 |
Q5_K_M | 5 | 2.7 GB | High | B64 |
Q6_K | 6 | 3.1 GB | High | B64 |
Q8_0 | 8 | 4.1 GB | Very High | B65 |
F16Best for your GPU | 16 | 7.8 GB | Maximum | B69 |
Copy-paste commands to run Phi 3 Mini 3.8B on your machine.
Run
ollama run phi3:miniYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | S | 37.9 tok/s | |
| Qwen 3 14B | 14B | S | 30.4 tok/s | |
| Qwen 3.5 4B | 4B | S | 64 tok/s | |
| Qwen 3 8B | 8B | S | 42.6 tok/s | |
 Phi-4-reasoning-plus 14B | 14.7B | S | 26 tok/s |
Yes, RTX 4060 Ti 16GB can run Phi 3 Mini 3.8B with a A grade (Runs well). Expected decode speed: 60.8 tok/s.
Phi 3 Mini 3.8B (3.799999952316284B parameters) requires approximately 10.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Phi 3 Mini 3.8B is Q4_K_M, which balances quality and memory efficiency.
On RTX 4060 Ti 16GB, Phi 3 Mini 3.8B achieves approximately 60.8 tokens per second decode speed with a time-to-first-token of 3184ms using Q4_K_M quantization.
For coding workloads, Phi 3 Mini 3.8B on RTX 4060 Ti 16GB receives a A grade with 60.8 tok/s and 31K context.
On RTX 4060 Ti 16GB, Phi 3 Mini 3.8B can safely use up to 31K 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-mini-3.8b-on-rtx-4060-ti-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: