Phi-4 Mini Reasoning 4B needs ~6.3 GB VRAM. RTX 5070 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~72 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
72.2 tok/s
TTFT
2681 ms
Safe context
122K
Memory
6.3 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 | S | Runs well | 72.2 tok/s | 1463 ms | 122K |
| Coding | S | Runs well | 72.2 tok/s | 2681 ms | 122K |
| Agentic Coding | S | Runs well | 72.2 tok/s | 3900 ms | 122K |
| Reasoning | S | Runs well | 72.2 tok/s | 3169 ms | 122K |
| RAG | S | Runs well | 72.2 tok/s | 4875 ms | 122K |
How Phi-4 Mini Reasoning 4B (3.799999952316284B params) fits at each quantization level on RTX 5070 Ti 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.5 GB | Low | A83 |
Q3_K_S | 3 | 1.9 GB | Low | A83 |
NVFP4 | 4 | 2.1 GB | Medium | A83 |
Q4_K_M | 4 | 2.3 GB | Medium | A84 |
Q5_K_M | 5 | 2.7 GB | High | A84 |
Q6_K | 6 | 3.1 GB | High | A84 |
Q8_0 | 8 | 4.1 GB | Very High | S85 |
F16Best for your GPU | 16 | 7.8 GB | Maximum | S89 |
Copy-paste commands to run Phi-4 Mini Reasoning 4B on your machine.
Run
ollama run phi4-miniYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 9B | S | 112.3 tok/s | ||
| 14B | S | 73.2 tok/s | ||
| 4B | S | 76 tok/s | ||
| 8B | S | 126.3 tok/s | ||
| 14.7B | S | 65.5 tok/s |
Yes, RTX 5070 Ti 16GB can run Phi-4 Mini Reasoning 4B with a S grade (Runs well). Expected decode speed: 72.2 tok/s.
Phi-4 Mini Reasoning 4B (3.799999952316284B parameters) requires approximately 6.3 GB of memory with Q4_K_M quantization.
The recommended quantization for Phi-4 Mini Reasoning 4B is Q4_K_M, which balances quality and memory efficiency.
On RTX 5070 Ti 16GB, Phi-4 Mini Reasoning 4B achieves approximately 72.2 tokens per second decode speed with a time-to-first-token of 2681ms using Q4_K_M quantization.
For coding workloads, Phi-4 Mini Reasoning 4B on RTX 5070 Ti 16GB receives a S grade with 72.2 tok/s and 122K context.
On RTX 5070 Ti 16GB, Phi-4 Mini Reasoning 4B can safely use up to 122K tokens of context. The model's official context limit is 131K, 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-4-mini-reasoning-on-rtx-5070-ti-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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