# Can I run Phi-4 14B on Nvidia GeForce RTX 5090 (32GB)?

> **Yes, it runs.** Runs at Q4_K_M using ~10.8 GB of ~31 GB usable. You have room for FP16 for higher quality.

Last validated: 2026-06-15.

## Memory math
- Phi-4 14B: 14B; Q4_K_M weighs 9.05 GB on disk.
- At Q4_K_M with a 4k context it needs ~10.8 GB (weights + KV cache + ~0.8 GB runtime overhead, ±15% with context length).
- Nvidia GeForce RTX 5090 (32GB): 32 GB vram, ~31 GB usable for model weights.
- Headroom: ~20.2 GB; it also fits FP16 for higher quality.

## How to run
Recommended quant: Q4_K_M. Best tool on Windows: LM Studio.

```sh
ollama run phi4:14b
```

## Run Phi-4 14B on other devices
- [Nvidia GeForce RTX 3060 (12GB)](https://localmodel.run/can-i-run/phi-4-14b/nvidia-rtx-3060-12gb)
- [Nvidia GeForce RTX 4070 (12GB)](https://localmodel.run/can-i-run/phi-4-14b/nvidia-rtx-4070-12gb)
- [Nvidia GeForce RTX 4060 Ti (16GB)](https://localmodel.run/can-i-run/phi-4-14b/nvidia-rtx-4060-ti-16gb)
- [Nvidia GeForce RTX 4080 (16GB)](https://localmodel.run/can-i-run/phi-4-14b/nvidia-rtx-4080-16gb)
- [16GB RAM Laptop (CPU/iGPU only)](https://localmodel.run/can-i-run/phi-4-14b/laptop-16gb)
- [iPad Pro M4 (16GB, 1TB/2TB config)](https://localmodel.run/can-i-run/phi-4-14b/ipad-pro-m4-16gb)

## Other models that run on Nvidia GeForce RTX 5090 (32GB)
- [Mixtral 8x7B (46.7B)](https://localmodel.run/can-i-run/mixtral-8x7b/nvidia-rtx-5090-32gb)
- [Command R 35B (35B)](https://localmodel.run/can-i-run/command-r-35b/nvidia-rtx-5090-32gb)
- [Yi 1.5 34B (34B)](https://localmodel.run/can-i-run/yi-1.5-34b/nvidia-rtx-5090-32gb)
- [Qwen2.5 32B (32B)](https://localmodel.run/can-i-run/qwen2.5-32b/nvidia-rtx-5090-32gb)
- [Qwen3 32B (32B)](https://localmodel.run/can-i-run/qwen3-32b/nvidia-rtx-5090-32gb)
- [DeepSeek-R1-Distill-Qwen 32B (32B)](https://localmodel.run/can-i-run/deepseek-r1-distill-qwen-32b/nvidia-rtx-5090-32gb)

Estimate, not a guarantee. Sources: https://ollama.com/library/phi4, https://ollama.com/library/phi4/tags, https://huggingface.co/bartowski/phi-4-GGUF, https://lmarena.ai/leaderboard.
More: https://localmodel.run/can-i-run/phi-4-14b/nvidia-rtx-5090-32gb