Can Phi 4 Mini 4B run on GTX 1660 Super 6GB?
YES — With Offload
Phi 4 Mini 4B needs ~5.7 GB VRAM. GTX 1660 Super 6GB has 6.0 GB. With Q4_K_M quantization, expect ~56 tok/s.
Operating mode
Choose the run profile you care about
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
56.0 tok/s
TTFT
3457 ms
Safe context
19K
Memory
5.7 GB / 6.0 GB
Memory breakdown
See how fast it feels
What limits this setup
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.
Best improvement path
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Tight fit | 56.0 tok/s | 1886 ms | 19K |
| Coding | A | Runs with offload | 56.0 tok/s | 3457 ms | 19K |
| Agentic Coding | B | Very compromised (needs ~0.4 GB host RAM) | 40.2 tok/s | 7011 ms | 19K |
| Reasoning | A | Runs with offload | 56.0 tok/s | 4086 ms | 19K |
| RAG | B | Very compromised (needs ~0.4 GB host RAM) | 40.2 tok/s | 8764 ms | 19K |
Quantization options
How Phi 4 Mini 4B (4B params) fits at each quantization level on GTX 1660 Super 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 |
Get started
Copy-paste commands to run Phi 4 Mini 4B on your machine.
Run
ollama run phi4-miniYour hardware
More models your GTX 1660 Super 6GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 7B | B | 25 tok/s | ||
| 7B | B | 25 tok/s | ||
| 7B | B | 26 tok/s | ||
| 5.1B | A | 64.6 tok/s |
Frequently asked questions
Can GTX 1660 Super 6GB run Phi 4 Mini 4B?
Yes, GTX 1660 Super 6GB can run Phi 4 Mini 4B with a A grade (Runs with offload). Expected decode speed: 56.0 tok/s.
How much VRAM does Phi 4 Mini 4B need?
Phi 4 Mini 4B (4B parameters) requires approximately 5.7 GB of memory with Q4_K_M quantization.
What is the best quantization for Phi 4 Mini 4B?
The recommended quantization for Phi 4 Mini 4B is Q4_K_M, which balances quality and memory efficiency.
What speed will Phi 4 Mini 4B run at on GTX 1660 Super 6GB?
On GTX 1660 Super 6GB, Phi 4 Mini 4B achieves approximately 56.0 tokens per second decode speed with a time-to-first-token of 3457ms using Q4_K_M quantization.
Can GTX 1660 Super 6GB run Phi 4 Mini 4B for coding?
For coding workloads, Phi 4 Mini 4B on GTX 1660 Super 6GB receives a A grade with 56.0 tok/s and 19K context.
What context window can Phi 4 Mini 4B use on GTX 1660 Super 6GB?
On GTX 1660 Super 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.
What should I upgrade first if Phi 4 Mini 4B feels slow on GTX 1660 Super 6GB?
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
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