Phi 4 Mini 4B needs ~5.7 GB VRAM. GTX 1060 6GB has 6.0 GB. With Q4_K_M quantization, expect ~50 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 with offload
Decode
49.9 tok/s
TTFT
3879 ms
Safe context
19K
Memory
5.7 GB / 6.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Older PCIe generation
PCIe 3.0 is workable, but it compounds the penalty when you offload heavily or try to scale across multiple cards.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Tight fit | 49.9 tok/s | 2116 ms | 19K |
| Coding | A | Runs with offload | 49.9 tok/s | 3879 ms | 19K |
| Agentic Coding | C | Very compromised (needs ~0.4 GB host RAM) | 24.6 tok/s | 11438 ms | 19K |
| Reasoning | A | Runs with offload | 49.9 tok/s | 4584 ms | 19K |
| RAG | C | Very compromised (needs ~0.4 GB host RAM) | 24.6 tok/s | 14297 ms | 19K |
How Phi 4 Mini 4B (4B params) fits at each quantization level on GTX 1060 6GB (6.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.6 GB | Low | A75 |
Q3_K_S | 3 | 2.0 GB | Low | A75 |
NVFP4 | 4 | 2.2 GB | Medium | A75 |
Q4_K_M | 4 | 2.4 GB | Medium | A75 |
Q5_K_M | 5 | 2.9 GB | High | A75 |
Q6_KBest for your GPU | 6 | 3.3 GB | High | A74 |
Q8_0 | 8 | 4.3 GB | Very High | F0 |
F16 | 16 | 8.2 GB | Maximum | F0 |
Copy-paste commands to run Phi 4 Mini 4B on your machine.
Run
ollama run phi4-miniYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 2.5 VL 7B | 7B | B | 15.3 tok/s | |
| Qwen 2.5 7B | 7B | B | 15.3 tok/s | |
 Codestral Mamba 7B | 7B | B | 15.9 tok/s | |
 Gemma 4 E2B | 5.1B | A | 39.6 tok/s |
Yes, GTX 1060 6GB can run Phi 4 Mini 4B with a A grade (Runs with offload). Expected decode speed: 49.9 tok/s.
Phi 4 Mini 4B (4B parameters) requires approximately 5.7 GB of memory with Q4_K_M quantization.
The recommended quantization for Phi 4 Mini 4B is Q4_K_M, which balances quality and memory efficiency.
On GTX 1060 6GB, Phi 4 Mini 4B achieves approximately 49.9 tokens per second decode speed with a time-to-first-token of 3879ms using Q4_K_M quantization.
For coding workloads, Phi 4 Mini 4B on GTX 1060 6GB receives a A grade with 49.9 tok/s and 19K context.
On GTX 1060 6GB, Phi 4 Mini 4B can safely use up to 19K tokens of context. The model's official context limit is 128K, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/phi-4-mini-4b-on-gtx-1060-6gb" 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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