Can I run it?
Can I run Phi 4 mini instruct on GeForce RTX 4060 Ti 16GB?
Runs great
Runs great fully on your GeForce RTX 4060 Ti 16GB at BF16, 8K context, about 18–25 tok/s. Weights 7.15 GB plus 1.00 GB of KV cache — 8.52 GB of 14.7 GB usable. Up to 32K context still fits.
Best quantBF16
Working context8K
Max that fits32K
Speed18–25 tok/s
Weights7.15 GB
KV cache1.00 GB
Total8.52 GB
Usable14.7 GB
Phi 4 mini instruct details · GeForce RTX 4060 Ti 16GB page · How this estimate is made
Run commands
llama.cpp
llama-server -hf unsloth/Phi-4-mini-instruct-GGUF:BF16 -c 8192 -ngl 32
Ollama
ollama run phi
LM Studio
lms get unsloth/Phi-4-mini-instruct-GGUF # Then load quant BF16
Assumptions
- Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
- KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
- BF16 size is the real GGUF file size from Hugging Face.
- 0.5 GB is reserved because this GPU also drives a display, then 5% of the rest is left free.
- Speed is quoted at 8K context, not at the maximum context that still fits.
Larger models that also fit
- Can I run Qwen3.8 27B on GeForce RTX 4060 Ti 16GB? — Tight fit, UD-IQ4_XS, 11–15 tok/s
- Can I run gemma 4 12b it on GeForce RTX 4060 Ti 16GB? — Tight fit, UD-Q8_K_XL, 9.4–13 tok/s
- Can I run Qwen3.5 9B on GeForce RTX 4060 Ti 16GB? — Tight fit, UD-Q8_K_XL, 12–16 tok/s
Updated 2026-10-17. Profile on this page is the device default plus 32 GB of DDR5-5600 system RAM.